Systems and methods for monitoring vehicle occupants

ABSTRACT

Techniques are disclosed for systems and methods using small form factor infrared imaging modules to monitor occupants in an interior compartment of a vehicle. For example, a vehicle-mounted system may include one or more infrared imaging modules, a processor, a memory, alarm sirens, and a communication module. The vehicle-mounted system may be mounted on, installed in, or otherwise integrated into a vehicle with an interior compartment. The infrared imaging modules may be configured to capture thermal images of desired portions of the interior compartments. Various thermal image processing and analytics may be performed on the captured thermal images to determine the presence and various attributes of one or more occupants. Based on the determination of the presence and various attributes, occupant detection information or control signals may be generated. Occupant detection information may be used to perform various monitoring operations, and control signals may adjust various vehicle components.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of U.S. patent applicationSer. No. 14/097,197 filed Dec. 4, 2013 and entitled “SYSTEMS AND METHODSFOR MONITORING VEHICLE OCCUPANTS,” which is hereby incorporated byreference in its entirety.

U.S. patent application Ser. No. 14/097,197 is a continuation of U.S.patent application Ser. No. 13/902,177 filed May 24, 2013, which claimsthe benefit of U.S. Provisional Patent Application No. 61/652,030 filedMay 25, 2012 and entitled “SYSTEMS AND METHODS FOR MONITORING VEHICLEOCCUPANTS,” which are all hereby incorporated by reference in theirentirety.

U.S. patent application Ser. No. 14/097,197 is a continuation-in-part ofInternational Patent Application No. PCT/US2012/041744 filed Jun. 8,2012 and entitled “LOW POWER AND SMALL FORM FACTOR INFRARED IMAGING,”which is incorporated herein by reference in its entirety.

International Patent Application No. PCT/US2012/041744 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/656,889filed Jun. 7, 2012 and entitled “LOW POWER AND SMALL FORM FACTORINFRARED IMAGING,” which are incorporated herein by reference in theirentirety.

International Patent Application No. PCT/US2012/041744 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/545,056filed Oct. 7, 2011 and entitled “NON-UNIFORMITY CORRECTION TECHNIQUESFOR INFRARED IMAGING DEVICES,” which are incorporated herein byreference in their entirety.

International Patent Application No. PCT/US2012/041744 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,873filed Jun. 10, 2011 and entitled “INFRARED CAMERA PACKAGING SYSTEMS ANDMETHODS,” which are incorporated herein by reference in their entirety.

International Patent Application No. PCT/US2012/041744 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,879filed Jun. 10, 2011 and entitled “INFRARED CAMERA SYSTEM ARCHITECTURES,”which are incorporated herein by reference in their entirety.

International Patent Application No. PCT/US2012/041744 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,888filed Jun. 10, 2011 and entitled “INFRARED CAMERA CALIBRATIONTECHNIQUES,” which are incorporated herein by reference in theirentirety.

U.S. patent application Ser. No. 14/097,197 is a continuation-in-part ofInternational Patent Application No. PCT/US2012/041749 filed Jun. 8,2012 and entitled “NON-UNIFORMITY CORRECTION TECHNIQUES FOR INFRAREDIMAGING DEVICES,” which is incorporated herein by reference in itsentirety.

International Patent Application No. PCT/US2012/041749 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/545,056filed Oct. 7, 2011 and entitled “NON-UNIFORMITY CORRECTION TECHNIQUESFOR INFRARED IMAGING DEVICES,” which are incorporated herein byreference in their entirety.

International Patent Application No. PCT/US2012/041749 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,873filed Jun. 10, 2011 and entitled “INFRARED CAMERA PACKAGING SYSTEMS ANDMETHODS,” which are incorporated herein by reference in their entirety.

International Patent Application No. PCT/US2012/041749 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,879filed Jun. 10, 2011 and entitled “INFRARED CAMERA SYSTEM ARCHITECTURES,”which are incorporated herein by reference in their entirety.

International Patent Application No. PCT/US2012/041749 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,888filed Jun. 10, 2011 and entitled “INFRARED CAMERA CALIBRATIONTECHNIQUES,” which are incorporated herein by reference in theirentirety.

U.S. patent application Ser. No. 14/097,197 is a continuation-in-part ofInternational Patent Application No. PCT/US2012/041739 filed Jun. 8,2012 and entitled “INFRARED CAMERA SYSTEM ARCHITECTURES,” which ishereby incorporated by reference in its entirety.

International Patent Application No. PCT/US2012/041739 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,873filed Jun. 10, 2011 and entitled “INFRARED CAMERA PACKAGING SYSTEMS ANDMETHODS,” which are incorporated herein by reference in their entirety.

International Patent Application No. PCT/US2012/041739 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,879filed Jun. 10, 2011 and entitled “INFRARED CAMERA SYSTEM ARCHITECTURES,”which are incorporated herein by reference in their entirety.

International Patent Application No. PCT/US2012/041739 claims priorityto and the benefit of U.S. Provisional Patent Application No. 61/495,888filed Jun. 10, 2011 and entitled “INFRARED CAMERA CALIBRATIONTECHNIQUES,” which are incorporated herein by reference in theirentirety.

U.S. patent application Ser. No. 14/097,197 is a continuation-in-part ofU.S. patent application Ser. No. 13/622,178 filed Sep. 18, 2012 andentitled “SYSTEMS AND METHODS FOR PROCESSING INFRARED IMAGES,” which isa continuation-in-part of U.S. patent application Ser. No. 13/529,772filed Jun. 21, 2012 and entitled “SYSTEMS AND METHODS FOR PROCESSINGINFRARED IMAGES,” which is a continuation of U.S. patent applicationSer. No. 12/396,340 filed Mar. 2, 2009 and entitled “SYSTEMS AND METHODSFOR PROCESSING INFRARED IMAGES,” which are incorporated herein byreference in their entirety.

TECHNICAL FIELD

One or more embodiments of the invention relate generally to thermalimaging devices and more particularly, for example, to the use ofthermal images to monitor occupants in a vehicle.

BACKGROUND

Many modern vehicles are equipped with reactive passenger restraintssuch as airbags, seatbelt tensioners, or other reactive restraints thatare activated in an event of a collision to mitigate injury tooccupants. To control deployment or activation of such reactiverestraints, various types of occupancy sensors are typically installedin vehicles. For example, weight or pressure sensors are incorporatedinto seats to detect whether or not an occupant is present in aparticular seat. In another example, various types of transducers, suchas ultrasonic sensors, microwave sensors, active infrared rangefinders,and capacitive proximity sensors, have been proposed as refinements overweight sensors. Such transducers are typically required to be installedin large numbers (e.g., three to four per each occupant seat), atmultiple locations, and in combination with various other types ofsensors in order to detect some positional information of occupants.

However, such conventional occupancy sensors, even when many of them areused in combination, are still prone to false or failed detections,since they are easily tricked by non-human objects or are sensitive toambient conditions such as humidity. Furthermore, such conventionaloccupancy sensors cannot provide occupant-related information other thanan indication of presence and some limited positional information. Asemphasis on vehicle safety and automation continues to grow, morecomprehensive and detailed occupant-related information may be needed toautomate various vehicle components, provide comprehensive monitoring,or otherwise improve safety and comfort of drivers and occupants.

SUMMARY

Various techniques are disclosed for systems and methods using smallform factor infrared imaging modules to monitor occupants in an interiorcompartment of a vehicle. For example, a vehicle-mounted system mayinclude one or more infrared imaging modules, a processor, a memory,alarm sirens, and a communication module. The vehicle-mounted system maybe mounted on, installed in, or otherwise integrated into a vehicle thathas an interior compartment. The infrared imaging modules may beconfigured to capture thermal images of desired portions of the interiorcompartments. Various thermal image processing and analytics may beperformed on the captured thermal images to determine the presence andvarious attributes of one or more occupants. Based on the determinationof the presence and various attributes, occupant detection informationand/or control signals may be generated. Occupant detection informationmay be used to perform various monitoring operations, and controlsignals may adjust various vehicle components.

In one embodiment, a vehicle includes an interior compartment; aninfrared imaging module comprising a focal plane array (FPA) configuredto capture thermal images of at least a portion of the interiorcompartment; and a processor configured to analyze the thermal images todetermine a presence of one or more occupants and one or more attributesassociated with the one or more occupants, and generate occupantdetection information based on the determination of the presence and theattributes of the one or more occupants.

In another embodiment, a vehicle includes an interior compartment; anadjustable component responsive to a control signal; an infrared imagingmodule comprising an FPA configured to capture thermal images of atleast a portion of the interior compartment; and a processor configuredto analyze the thermal images to determine a presence of one or moreoccupants and one or more attributes associated with the one or moreoccupants, and generate the control signal based on the determination ofthe presence and the attributes of the one or more occupants.

In another embodiment, a method includes capturing, at an FPA of aninfrared imaging module, thermal images of at least a portion of aninterior compartment of a vehicle, wherein the infrared imaging moduleis mounted in or on the vehicle so that the at least a portion of theinterior compartment is within a field of view (FOV) of the infraredimaging module; analyzing the thermal images to determine a presence ofone or more occupants and one or more attributes associated with the oneor more occupants; and generating occupant detection information basedon the determination of the presence and the attributes of the one ormore occupants.

In another embodiment, a method includes capturing, at an FPA of aninfrared imaging module, thermal images of at least a portion of aninterior compartment of a vehicle, wherein the infrared imaging moduleis mounted in or on the vehicle so that the at least a portion of theinterior compartment is within an FOV of the infrared imaging module;analyzing the thermal images to determine a presence of one or moreoccupants and one or more attributes associated with the one or moreoccupants; generating a control signal for an adjustable component ofthe vehicle based on the determination of the presence and theattributes of the one or more occupants; and providing the controlsignal to the adjustable component.

The scope of the invention is defined by the claims, which areincorporated into this section by reference. A more completeunderstanding of embodiments of the invention will be afforded to thoseskilled in the art, as well as a realization of additional advantagesthereof, by a consideration of the following detailed description of oneor more embodiments. Reference will be made to the appended sheets ofdrawings that will first be described briefly.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an infrared imaging module configured to beimplemented in a host device in accordance with an embodiment of thedisclosure.

FIG. 2 illustrates an assembled infrared imaging module in accordancewith an embodiment of the disclosure.

FIG. 3 illustrates an exploded view of an infrared imaging modulejuxtaposed over a socket in accordance with an embodiment of thedisclosure.

FIG. 4 illustrates a block diagram of infrared sensor assembly includingan array of infrared sensors in accordance with an embodiment of thedisclosure.

FIG. 5 illustrates a flow diagram of various operations to determine NUCterms in accordance with an embodiment of the disclosure.

FIG. 6 illustrates differences between neighboring pixels in accordancewith an embodiment of the disclosure.

FIG. 7 illustrates a flat field correction technique in accordance withan embodiment of the disclosure.

FIG. 8 illustrates various image processing techniques of FIG. 5 andother operations applied in an image processing pipeline in accordancewith an embodiment of the disclosure.

FIG. 9 illustrates a temporal noise reduction process in accordance withan embodiment of the disclosure.

FIG. 10 illustrates particular implementation details of severalprocesses of the image processing pipeline of FIG. 6 in accordance withan embodiment of the disclosure.

FIG. 11 illustrates spatially correlated FPN in a neighborhood of pixelsin accordance with an embodiment of the disclosure.

FIG. 12 illustrates a block diagram of a vehicle-mounted system formonitoring occupants in an interior compartment of a vehicle inaccordance with an embodiment of the disclosure.

FIGS. 13A-13B illustrate various views of a vehicle having avehicle-mounted system for monitoring occupants in an interiorcompartment in accordance with an embodiment of the disclosure.

FIG. 14 illustrates a process for monitoring occupants in an interiorcompartment of a vehicle in accordance with an embodiment of thedisclosure.

FIG. 15 illustrates a process for performing various monitoringoperations based on occupant detection information in accordance with anembodiment of the disclosure.

Embodiments of the invention and their advantages are best understood byreferring to the detailed description that follows. It should beappreciated that like reference numerals are used to identify likeelements illustrated in one or more of the figures.

DETAILED DESCRIPTION

FIG. 1 illustrates an infrared imaging module 100 (e.g., an infraredcamera or an infrared imaging device) configured to be implemented in ahost device 102 in accordance with an embodiment of the disclosure.Infrared imaging module 100 may be implemented, for one or moreembodiments, with a small form factor and in accordance with wafer levelpackaging techniques or other packaging techniques.

In one embodiment, infrared imaging module 100 may be configured to beimplemented in a small portable host device 102, such as a mobiletelephone, a tablet computing device, a laptop computing device, apersonal digital assistant, a visible light camera, a music player, orany other appropriate mobile device. In this regard, infrared imagingmodule 100 may be used to provide infrared imaging features to hostdevice 102. For example, infrared imaging module 100 may be configuredto capture, process, and/or otherwise manage infrared images and providesuch infrared images to host device 102 for use in any desired fashion(e.g., for further processing, to store in memory, to display, to use byvarious applications running on host device 102, to export to otherdevices, or other uses).

In various embodiments, infrared imaging module 100 may be configured tooperate at low voltage levels and over a wide temperature range. Forexample, in one embodiment, infrared imaging module 100 may operateusing a power supply of approximately 2.4 volts, 2.5 volts, 2.8 volts,or lower voltages, and operate over a temperature range of approximately−20 degrees C. to approximately +60 degrees C. (e.g., providing asuitable dynamic range and performance over an environmental temperaturerange of approximately 80 degrees C.). In one embodiment, by operatinginfrared imaging module 100 at low voltage levels, infrared imagingmodule 100 may experience reduced amounts of self heating in comparisonwith other types of infrared imaging devices. As a result, infraredimaging module 100 may be operated with reduced measures to compensatefor such self heating.

As shown in FIG. 1, host device 102 may include a socket 104, a shutter105, motion sensors 194, a processor 195, a memory 196, a display 197,and/or other components 198. Socket 104 may be configured to receiveinfrared imaging module 100 as identified by arrow 101. In this regard,FIG. 2 illustrates infrared imaging module 100 assembled in socket 104in accordance with an embodiment of the disclosure.

Motion sensors 194 may be implemented by one or more accelerometers,gyroscopes, or other appropriate devices that may be used to detectmovement of host device 102. Motion sensors 194 may be monitored by andprovide information to processing module 160 or processor 195 to detectmotion. In various embodiments, motion sensors 194 may be implemented aspart of host device 102 (as shown in FIG. 1), infrared imaging module100, or other devices attached to or otherwise interfaced with hostdevice 102.

Processor 195 may be implemented as any appropriate processing device(e.g., logic device, microcontroller, processor, application specificintegrated circuit (ASIC), or other device) that may be used by hostdevice 102 to execute appropriate instructions, such as softwareinstructions provided in memory 196. Display 197 may be used to displaycaptured and/or processed infrared images and/or other images, data, andinformation. Other components 198 may be used to implement any featuresof host device 102 as may be desired for various applications (e.g.,clocks, temperature sensors, a visible light camera, or othercomponents). In addition, a machine readable medium 193 may be providedfor storing non-transitory instructions for loading into memory 196 andexecution by processor 195.

In various embodiments, infrared imaging module 100 and socket 104 maybe implemented for mass production to facilitate high volumeapplications, such as for implementation in mobile telephones or otherdevices (e.g., requiring small form factors). In one embodiment, thecombination of infrared imaging module 100 and socket 104 may exhibitoverall dimensions of approximately 8.5 mm by 8.5 mm by 5.9 mm whileinfrared imaging module 100 is installed in socket 104.

FIG. 3 illustrates an exploded view of infrared imaging module 100juxtaposed over socket 104 in accordance with an embodiment of thedisclosure. Infrared imaging module 100 may include a lens barrel 110, ahousing 120, an infrared sensor assembly 128, a circuit board 170, abase 150, and a processing module 160.

Lens barrel 110 may at least partially enclose an optical element 180(e.g., a lens) which is partially visible in FIG. 3 through an aperture112 in lens barrel 110. Lens barrel 110 may include a substantiallycylindrical extension 114 which may be used to interface lens barrel 110with an aperture 122 in housing 120.

Infrared sensor assembly 128 may be implemented, for example, with a cap130 (e.g., a lid) mounted on a substrate 140. Infrared sensor assembly128 may include a plurality of infrared sensors 132 (e.g., infrareddetectors) implemented in an array or other fashion on substrate 140 andcovered by cap 130. For example, in one embodiment, infrared sensorassembly 128 may be implemented as a focal plane array (FPA). Such afocal plane array may be implemented, for example, as a vacuum packageassembly (e.g., sealed by cap 130 and substrate 140). In one embodiment,infrared sensor assembly 128 may be implemented as a wafer level package(e.g., infrared sensor assembly 128 may be singulated from a set ofvacuum package assemblies provided on a wafer). In one embodiment,infrared sensor assembly 128 may be implemented to operate using a powersupply of approximately 2.4 volts, 2.5 volts, 2.8 volts, or similarvoltages.

Infrared sensors 132 may be configured to detect infrared radiation(e.g., infrared energy) from a target scene including, for example, midwave infrared wave bands (MWIR), long wave infrared wave bands (LWIR),and/or other thermal imaging bands as may be desired in particularimplementations. In one embodiment, infrared sensor assembly 128 may beprovided in accordance with wafer level packaging techniques.

Infrared sensors 132 may be implemented, for example, as microbolometersor other types of thermal imaging infrared sensors arranged in anydesired array pattern to provide a plurality of pixels. In oneembodiment, infrared sensors 132 may be implemented as vanadium oxide(VOx) detectors with a 17 μm pixel pitch. In various embodiments, arraysof approximately 32 by 32 infrared sensors 132, approximately 64 by 64infrared sensors 132, approximately 80 by 64 infrared sensors 132, orother array sizes may be used.

Substrate 140 may include various circuitry including, for example, aread out integrated circuit (ROIC) with dimensions less thanapproximately 5.5 mm by 5.5 mm in one embodiment. Substrate 140 may alsoinclude bond pads 142 that may be used to contact complementaryconnections positioned on inside surfaces of housing 120 when infraredimaging module 100 is assembled as shown in FIGS. 5A, 5B, and 5C. In oneembodiment, the ROIC may be implemented with low-dropout regulators(LDO) to perform voltage regulation to reduce power supply noiseintroduced to infrared sensor assembly 128 and thus provide an improvedpower supply rejection ratio (PSRR). Moreover, by implementing the LDOwith the ROIC (e.g., within a wafer level package), less die area may beconsumed and fewer discrete die (or chips) are needed.

FIG. 4 illustrates a block diagram of infrared sensor assembly 128including an array of infrared sensors 132 in accordance with anembodiment of the disclosure. In the illustrated embodiment, infraredsensors 132 are provided as part of a unit cell array of a ROIC 402.ROIC 402 includes bias generation and timing control circuitry 404,column amplifiers 405, a column multiplexer 406, a row multiplexer 408,and an output amplifier 410. Image frames (e.g., thermal images)captured by infrared sensors 132 may be provided by output amplifier 410to processing module 160, processor 195, and/or any other appropriatecomponents to perform various processing techniques described herein.Although an 8 by 8 array is shown in FIG. 4, any desired arrayconfiguration may be used in other embodiments. Further descriptions ofROICs and infrared sensors (e.g., microbolometer circuits) may be foundin U.S. Pat. No. 6,028,309 issued Feb. 22, 2000, which is incorporatedherein by reference in its entirety.

Infrared sensor assembly 128 may capture images (e.g., image frames) andprovide such images from its ROIC at various rates. Processing module160 may be used to perform appropriate processing of captured infraredimages and may be implemented in accordance with any appropriatearchitecture. In one embodiment, processing module 160 may beimplemented as an ASIC. In this regard, such an ASIC may be configuredto perform image processing with high performance and/or highefficiency. In another embodiment, processing module 160 may beimplemented with a general purpose central processing unit (CPU) whichmay be configured to execute appropriate software instructions toperform image processing, coordinate and perform image processing withvarious image processing blocks, coordinate interfacing betweenprocessing module 160 and host device 102, and/or other operations. Inyet another embodiment, processing module 160 may be implemented with afield programmable gate array (FPGA). Processing module 160 may beimplemented with other types of processing and/or logic circuits inother embodiments as would be understood by one skilled in the art.

In these and other embodiments, processing module 160 may also beimplemented with other components where appropriate, such as, volatilememory, non-volatile memory, and/or one or more interfaces (e.g.,infrared detector interfaces, inter-integrated circuit (I2C) interfaces,mobile industry processor interfaces (MIPI), joint test action group(JTAG) interfaces (e.g., IEEE 1149.1 standard test access port andboundary-scan architecture), and/or other interfaces).

In some embodiments, infrared imaging module 100 may further include oneor more actuators 199 which may be used to adjust the focus of infraredimage frames captured by infrared sensor assembly 128. For example,actuators 199 may be used to move optical element 180, infrared sensors132, and/or other components relative to each other to selectively focusand defocus infrared image frames in accordance with techniquesdescribed herein. Actuators 199 may be implemented in accordance withany type of motion-inducing apparatus or mechanism, and may positionedat any location within or external to infrared imaging module 100 asappropriate for different applications.

When infrared imaging module 100 is assembled, housing 120 maysubstantially enclose infrared sensor assembly 128, base 150, andprocessing module 160. Housing 120 may facilitate connection of variouscomponents of infrared imaging module 100. For example, in oneembodiment, housing 120 may provide electrical connections 126 toconnect various components as further described.

Electrical connections 126 (e.g., conductive electrical paths, traces,or other types of connections) may be electrically connected with bondpads 142 when infrared imaging module 100 is assembled. In variousembodiments, electrical connections 126 may be embedded in housing 120,provided on inside surfaces of housing 120, and/or otherwise provided byhousing 120. Electrical connections 126 may terminate in connections 124protruding from the bottom surface of housing 120 as shown in FIG. 3.Connections 124 may connect with circuit board 170 when infrared imagingmodule 100 is assembled (e.g., housing 120 may rest atop circuit board170 in various embodiments). Processing module 160 may be electricallyconnected with circuit board 170 through appropriate electricalconnections. As a result, infrared sensor assembly 128 may beelectrically connected with processing module 160 through, for example,conductive electrical paths provided by: bond pads 142, complementaryconnections on inside surfaces of housing 120, electrical connections126 of housing 120, connections 124, and circuit board 170.Advantageously, such an arrangement may be implemented without requiringwire bonds to be provided between infrared sensor assembly 128 andprocessing module 160.

In various embodiments, electrical connections 126 in housing 120 may bemade from any desired material (e.g., copper or any other appropriateconductive material). In one embodiment, electrical connections 126 mayaid in dissipating heat from infrared imaging module 100.

Other connections may be used in other embodiments. For example, in oneembodiment, sensor assembly 128 may be attached to processing module 160through a ceramic board that connects to sensor assembly 128 by wirebonds and to processing module 160 by a ball grid array (BGA). Inanother embodiment, sensor assembly 128 may be mounted directly on arigid flexible board and electrically connected with wire bonds, andprocessing module 160 may be mounted and connected to the rigid flexibleboard with wire bonds or a BGA.

The various implementations of infrared imaging module 100 and hostdevice 102 set forth herein are provided for purposes of example, ratherthan limitation. In this regard, any of the various techniques describedherein may be applied to any infrared camera system, infrared imager, orother device for performing infrared/thermal imaging.

Substrate 140 of infrared sensor assembly 128 may be mounted on base150. In various embodiments, base 150 (e.g., a pedestal) may be made,for example, of copper formed by metal injection molding (MIM) andprovided with a black oxide or nickel-coated finish. In variousembodiments, base 150 may be made of any desired material, such as forexample zinc, aluminum, or magnesium, as desired for a given applicationand may be formed by any desired applicable process, such as for examplealuminum casting, MIM, or zinc rapid casting, as may be desired forparticular applications. In various embodiments, base 150 may beimplemented to provide structural support, various circuit paths,thermal heat sink properties, and other features where appropriate. Inone embodiment, base 150 may be a multi-layer structure implemented atleast in part using ceramic material.

In various embodiments, circuit board 170 may receive housing 120 andthus may physically support the various components of infrared imagingmodule 100. In various embodiments, circuit board 170 may be implementedas a printed circuit board (e.g., an FR4 circuit board or other types ofcircuit boards), a rigid or flexible interconnect (e.g., tape or othertype of interconnects), a flexible circuit substrate, a flexible plasticsubstrate, or other appropriate structures. In various embodiments, base150 may be implemented with the various features and attributesdescribed for circuit board 170, and vice versa.

Socket 104 may include a cavity 106 configured to receive infraredimaging module 100 (e.g., as shown in the assembled view of FIG. 2).Infrared imaging module 100 and/or socket 104 may include appropriatetabs, arms, pins, fasteners, or any other appropriate engagement memberswhich may be used to secure infrared imaging module 100 to or withinsocket 104 using friction, tension, adhesion, and/or any otherappropriate manner. Socket 104 may include engagement members 107 thatmay engage surfaces 109 of housing 120 when infrared imaging module 100is inserted into a cavity 106 of socket 104. Other types of engagementmembers may be used in other embodiments.

Infrared imaging module 100 may be electrically connected with socket104 through appropriate electrical connections (e.g., contacts, pins,wires, or any other appropriate connections). For example, socket 104may include electrical connections 108 which may contact correspondingelectrical connections of infrared imaging module 100 (e.g.,interconnect pads, contacts, or other electrical connections on side orbottom surfaces of circuit board 170, bond pads 142 or other electricalconnections on base 150, or other connections). Electrical connections108 may be made from any desired material (e.g., copper or any otherappropriate conductive material). In one embodiment, electricalconnections 108 may be mechanically biased to press against electricalconnections of infrared imaging module 100 when infrared imaging module100 is inserted into cavity 106 of socket 104. In one embodiment,electrical connections 108 may at least partially secure infraredimaging module 100 in socket 104. Other types of electrical connectionsmay be used in other embodiments.

Socket 104 may be electrically connected with host device 102 throughsimilar types of electrical connections. For example, in one embodiment,host device 102 may include electrical connections (e.g., solderedconnections, snap-in connections, or other connections) that connectwith electrical connections 108 passing through apertures 190. Invarious embodiments, such electrical connections may be made to thesides and/or bottom of socket 104.

Various components of infrared imaging module 100 may be implementedwith flip chip technology which may be used to mount components directlyto circuit boards without the additional clearances typically needed forwire bond connections. Flip chip connections may be used, as an example,to reduce the overall size of infrared imaging module 100 for use incompact small form factor applications. For example, in one embodiment,processing module 160 may be mounted to circuit board 170 using flipchip connections. For example, infrared imaging module 100 may beimplemented with such flip chip configurations.

In various embodiments, infrared imaging module 100 and/or associatedcomponents may be implemented in accordance with various techniques(e.g., wafer level packaging techniques) as set forth in U.S. patentapplication Ser. No. 12/844,124 filed Jul. 27, 2010, and U.S.Provisional Patent Application No. 61/469,651 filed Mar. 30, 2011, whichare incorporated herein by reference in their entirety. Furthermore, inaccordance with one or more embodiments, infrared imaging module 100and/or associated components may be implemented, calibrated, tested,and/or used in accordance with various techniques, such as for exampleas set forth in U.S. Pat. No. 7,470,902 issued Dec. 30, 2008, U.S. Pat.No. 6,028,309 issued Feb. 22, 2000, U.S. Pat. No. 6,812,465 issued Nov.2, 2004, U.S. Pat. No. 7,034,301 issued Apr. 25, 2006, U.S. Pat. No.7,679,048 issued Mar. 16, 2010, U.S. Pat. No. 7,470,904 issued Dec. 30,2008, U.S. patent application Ser. No. 12/202,880 filed Sep. 2, 2008,and U.S. patent application Ser. No. 12/202,896 filed Sep. 2, 2008,which are incorporated herein by reference in their entirety.

Referring again to FIG. 1, in various embodiments, host device 102 mayinclude shutter 105. In this regard, shutter 105 may be selectivelypositioned over socket 104 (e.g., as identified by arrows 103) whileinfrared imaging module 100 is installed therein. In this regard,shutter 105 may be used, for example, to protect infrared imaging module100 when not in use. Shutter 105 may also be used as a temperaturereference as part of a calibration process (e.g., a NUC process or othercalibration processes) for infrared imaging module 100 as would beunderstood by one skilled in the art.

In various embodiments, shutter 105 may be made from various materialssuch as, for example, polymers, glass, aluminum (e.g., painted oranodized) or other materials. In various embodiments, shutter 105 mayinclude one or more coatings to selectively filter electromagneticradiation and/or adjust various optical properties of shutter 105 (e.g.,a uniform blackbody coating or a reflective gold coating).

In another embodiment, shutter 105 may be fixed in place to protectinfrared imaging module 100 at all times. In this case, shutter 105 or aportion of shutter 105 may be made from appropriate materials (e.g.,polymers or infrared transmitting materials such as silicon, germanium,zinc selenide, or chalcogenide glasses) that do not substantially filterdesired infrared wavelengths. In another embodiment, a shutter may beimplemented as part of infrared imaging module 100 (e.g., within or aspart of a lens barrel or other components of infrared imaging module100), as would be understood by one skilled in the art.

Alternatively, in another embodiment, a shutter (e.g., shutter 105 orother type of external or internal shutter) need not be provided, butrather a NUC process or other type of calibration may be performed usingshutterless techniques. In another embodiment, a NUC process or othertype of calibration using shutterless techniques may be performed incombination with shutter-based techniques.

Infrared imaging module 100 and host device 102 may be implemented inaccordance with any of the various techniques set forth in U.S.Provisional Patent Application No. 61/495,873 filed Jun. 10, 2011, U.S.Provisional Patent Application No. 61/495,879 filed Jun. 10, 2011, andU.S. Provisional Patent Application No. 61/495,888 filed Jun. 10, 2011,which are incorporated herein by reference in their entirety.

In various embodiments, the components of host device 102 and/orinfrared imaging module 100 may be implemented as a local or distributedsystem with components in communication with each other over wiredand/or wireless networks. Accordingly, the various operations identifiedin this disclosure may be performed by local and/or remote components asmay be desired in particular implementations.

FIG. 5 illustrates a flow diagram of various operations to determine NUCterms in accordance with an embodiment of the disclosure. In someembodiments, the operations of FIG. 5 may be performed by processingmodule 160 or processor 195 (both also generally referred to as aprocessor) operating on image frames captured by infrared sensors 132.

In block 505, infrared sensors 132 begin capturing image frames of ascene. Typically, the scene will be the real world environment in whichhost device 102 is currently located. In this regard, shutter 105 (ifoptionally provided) may be opened to permit infrared imaging module toreceive infrared radiation from the scene. Infrared sensors 132 maycontinue capturing image frames during all operations shown in FIG. 5.In this regard, the continuously captured image frames may be used forvarious operations as further discussed. In one embodiment, the capturedimage frames may be temporally filtered (e.g., in accordance with theprocess of block 826 further described herein with regard to FIG. 8) andbe processed by other terms (e.g., factory gain terms 812, factoryoffset terms 816, previously determined NUC terms 817, column FPN terms820, and row FPN terms 824 as further described herein with regard toFIG. 8) before they are used in the operations shown in FIG. 5.

In block 510, a NUC process initiating event is detected. In oneembodiment, the NUC process may be initiated in response to physicalmovement of host device 102. Such movement may be detected, for example,by motion sensors 194 which may be polled by a processor. In oneexample, a user may move host device 102 in a particular manner, such asby intentionally waving host device 102 back and forth in an “erase” or“swipe” movement. In this regard, the user may move host device 102 inaccordance with a predetermined speed and direction (velocity), such asin an up and down, side to side, or other pattern to initiate the NUCprocess. In this example, the use of such movements may permit the userto intuitively operate host device 102 to simulate the “erasing” ofnoise in captured image frames.

In another example, a NUC process may be initiated by host device 102 ifmotion exceeding a threshold value is exceeded (e.g., motion greaterthan expected for ordinary use). It is contemplated that any desiredtype of spatial translation of host device 102 may be used to initiatethe NUC process.

In yet another example, a NUC process may be initiated by host device102 if a minimum time has elapsed since a previously performed NUCprocess. In a further example, a NUC process may be initiated by hostdevice 102 if infrared imaging module 100 has experienced a minimumtemperature change since a previously performed NUC process. In a stillfurther example, a NUC process may be continuously initiated andrepeated.

In block 515, after a NUC process initiating event is detected, it isdetermined whether the NUC process should actually be performed. In thisregard, the NUC process may be selectively initiated based on whetherone or more additional conditions are met. For example, in oneembodiment, the NUC process may not be performed unless a minimum timehas elapsed since a previously performed NUC process. In anotherembodiment, the NUC process may not be performed unless infrared imagingmodule 100 has experienced a minimum temperature change since apreviously performed NUC process. Other criteria or conditions may beused in other embodiments. If appropriate criteria or conditions havebeen met, then the flow diagram continues to block 520. Otherwise, theflow diagram returns to block 505.

In the NUC process, blurred image frames may be used to determine NUCterms which may be applied to captured image frames to correct for FPN.As discussed, in one embodiment, the blurred image frames may beobtained by accumulating multiple image frames of a moving scene (e.g.,captured while the scene and/or the thermal imager is in motion). Inanother embodiment, the blurred image frames may be obtained bydefocusing an optical element or other component of the thermal imager.

Accordingly, in block 520 a choice of either approach is provided. Ifthe motion-based approach is used, then the flow diagram continues toblock 525. If the defocus-based approach is used, then the flow diagramcontinues to block 530.

Referring now to the motion-based approach, in block 525 motion isdetected. For example, in one embodiment, motion may be detected basedon the image frames captured by infrared sensors 132. In this regard, anappropriate motion detection process (e.g., an image registrationprocess, a frame-to-frame difference calculation, or other appropriateprocess) may be applied to captured image frames to determine whethermotion is present (e.g., whether static or moving image frames have beencaptured). For example, in one embodiment, it can be determined whetherpixels or regions around the pixels of consecutive image frames havechanged more than a user defined amount (e.g., a percentage and/orthreshold value). If at least a given percentage of pixels have changedby at least the user defined amount, then motion will be detected withsufficient certainty to proceed to block 535.

In another embodiment, motion may be determined on a per pixel basis,wherein only pixels that exhibit significant changes are accumulated toprovide the blurred image frame. For example, counters may be providedfor each pixel and used to ensure that the same number of pixel valuesare accumulated for each pixel, or used to average the pixel valuesbased on the number of pixel values actually accumulated for each pixel.Other types of image-based motion detection may be performed such asperforming a Radon transform.

In another embodiment, motion may be detected based on data provided bymotion sensors 194. In one embodiment, such motion detection may includedetecting whether host device 102 is moving along a relatively straighttrajectory through space. For example, if host device 102 is movingalong a relatively straight trajectory, then it is possible that certainobjects appearing in the imaged scene may not be sufficiently blurred(e.g., objects in the scene that may be aligned with or movingsubstantially parallel to the straight trajectory). Thus, in such anembodiment, the motion detected by motion sensors 194 may be conditionedon host device 102 exhibiting, or not exhibiting, particulartrajectories.

In yet another embodiment, both a motion detection process and motionsensors 194 may be used. Thus, using any of these various embodiments, adetermination can be made as to whether or not each image frame wascaptured while at least a portion of the scene and host device 102 werein motion relative to each other (e.g., which may be caused by hostdevice 102 moving relative to the scene, at least a portion of the scenemoving relative to host device 102, or both).

It is expected that the image frames for which motion was detected mayexhibit some secondary blurring of the captured scene (e.g., blurredthermal image data associated with the scene) due to the thermal timeconstants of infrared sensors 132 (e.g., microbolometer thermal timeconstants) interacting with the scene movement.

In block 535, image frames for which motion was detected areaccumulated. For example, if motion is detected for a continuous seriesof image frames, then the image frames of the series may be accumulated.As another example, if motion is detected for only some image frames,then the non-moving image frames may be skipped and not included in theaccumulation. Thus, a continuous or discontinuous set of image framesmay be selected to be accumulated based on the detected motion.

In block 540, the accumulated image frames are averaged to provide ablurred image frame. Because the accumulated image frames were capturedduring motion, it is expected that actual scene information will varybetween the image frames and thus cause the scene information to befurther blurred in the resulting blurred image frame (block 545).

In contrast, FPN (e.g., caused by one or more components of infraredimaging module 100) will remain fixed over at least short periods oftime and over at least limited changes in scene irradiance duringmotion. As a result, image frames captured in close proximity in timeand space during motion will suffer from identical or at least verysimilar FPN. Thus, although scene information may change in consecutiveimage frames, the FPN will stay essentially constant. By averaging,multiple image frames captured during motion will blur the sceneinformation, but will not blur the FPN. As a result, FPN will remainmore clearly defined in the blurred image frame provided in block 545than the scene information.

In one embodiment, 32 or more image frames are accumulated and averagedin blocks 535 and 540. However, any desired number of image frames maybe used in other embodiments, but with generally decreasing correctionaccuracy as frame count is decreased.

Referring now to the defocus-based approach, in block 530, a defocusoperation may be performed to intentionally defocus the image framescaptured by infrared sensors 132. For example, in one embodiment, one ormore actuators 199 may be used to adjust, move, or otherwise translateoptical element 180, infrared sensor assembly 128, and/or othercomponents of infrared imaging module 100 to cause infrared sensors 132to capture a blurred (e.g., unfocused) image frame of the scene. Othernon-actuator based techniques are also contemplated for intentionallydefocusing infrared image frames such as, for example, manual (e.g.,user-initiated) defocusing.

Although the scene may appear blurred in the image frame, FPN (e.g.,caused by one or more components of infrared imaging module 100) willremain unaffected by the defocusing operation. As a result, a blurredimage frame of the scene will be provided (block 545) with FPN remainingmore clearly defined in the blurred image than the scene information.

In the above discussion, the defocus-based approach has been describedwith regard to a single captured image frame. In another embodiment, thedefocus-based approach may include accumulating multiple image frameswhile the infrared imaging module 100 has been defocused and averagingthe defocused image frames to remove the effects of temporal noise andprovide a blurred image frame in block 545.

Thus, it will be appreciated that a blurred image frame may be providedin block 545 by either the motion-based approach or the defocus-basedapproach. Because much of the scene information will be blurred byeither motion, defocusing, or both, the blurred image frame may beeffectively considered a low pass filtered version of the originalcaptured image frames with respect to scene information.

In block 550, the blurred image frame is processed to determine updatedrow and column FPN terms (e.g., if row and column FPN terms have notbeen previously determined then the updated row and column FPN terms maybe new row and column FPN terms in the first iteration of block 550). Asused in this disclosure, the terms row and column may be usedinterchangeably depending on the orientation of infrared sensors 132and/or other components of infrared imaging module 100.

In one embodiment, block 550 includes determining a spatial FPNcorrection term for each row of the blurred image frame (e.g., each rowmay have its own spatial FPN correction term), and also determining aspatial FPN correction term for each column of the blurred image frame(e.g., each column may have its own spatial FPN correction term). Suchprocessing may be used to reduce the spatial and slowly varying (1/f)row and column FPN inherent in thermal imagers caused by, for example,1/f noise characteristics of amplifiers in ROIC 402 which may manifestas vertical and horizontal stripes in image frames.

Advantageously, by determining spatial row and column FPN terms usingthe blurred image frame, there will be a reduced risk of vertical andhorizontal objects in the actual imaged scene from being mistaken forrow and column noise (e.g., real scene content will be blurred while FPNremains unblurred).

In one embodiment, row and column FPN terms may be determined byconsidering differences between neighboring pixels of the blurred imageframe. For example, FIG. 6 illustrates differences between neighboringpixels in accordance with an embodiment of the disclosure. Specifically,in FIG. 6 a pixel 610 is compared to its 8 nearest horizontal neighbors:d0-d3 on one side and d4-d7 on the other side. Differences between theneighbor pixels can be averaged to obtain an estimate of the offseterror of the illustrated group of pixels. An offset error may becalculated for each pixel in a row or column and the average result maybe used to correct the entire row or column.

To prevent real scene data from being interpreted as noise, upper andlower threshold values may be used (thPix and −thPix). Pixel valuesfalling outside these threshold values (pixels d1 and d4 in thisexample) are not used to obtain the offset error. In addition, themaximum amount of row and column FPN correction may be limited by thesethreshold values.

Further techniques for performing spatial row and column FPN correctionprocessing are set forth in U.S. patent application Ser. No. 12/396,340filed Mar. 2, 2009 which is incorporated herein by reference in itsentirety.

Referring again to FIG. 5, the updated row and column FPN termsdetermined in block 550 are stored (block 552) and applied (block 555)to the blurred image frame provided in block 545. After these terms areapplied, some of the spatial row and column FPN in the blurred imageframe may be reduced. However, because such terms are applied generallyto rows and columns, additional FPN may remain such as spatiallyuncorrelated FPN associated with pixel to pixel drift or other causes.Neighborhoods of spatially correlated FPN may also remain which may notbe directly associated with individual rows and columns. Accordingly,further processing may be performed as discussed below to determine NUCterms.

In block 560, local contrast values (e.g., edges or absolute values ofgradients between adjacent or small groups of pixels) in the blurredimage frame are determined. If scene information in the blurred imageframe includes contrasting areas that have not been significantlyblurred (e.g., high contrast edges in the original scene data), thensuch features may be identified by a contrast determination process inblock 560.

For example, local contrast values in the blurred image frame may becalculated, or any other desired type of edge detection process may beapplied to identify certain pixels in the blurred image as being part ofan area of local contrast. Pixels that are marked in this manner may beconsidered as containing excessive high spatial frequency sceneinformation that would be interpreted as FPN (e.g., such regions maycorrespond to portions of the scene that have not been sufficientlyblurred). As such, these pixels may be excluded from being used in thefurther determination of NUC terms. In one embodiment, such contrastdetection processing may rely on a threshold that is higher than theexpected contrast value associated with FPN (e.g., pixels exhibiting acontrast value higher than the threshold may be considered to be sceneinformation, and those lower than the threshold may be considered to beexhibiting FPN).

In one embodiment, the contrast determination of block 560 may beperformed on the blurred image frame after row and column FPN terms havebeen applied to the blurred image frame (e.g., as shown in FIG. 5). Inanother embodiment, block 560 may be performed prior to block 550 todetermine contrast before row and column FPN terms are determined (e.g.,to prevent scene based contrast from contributing to the determinationof such terms).

Following block 560, it is expected that any high spatial frequencycontent remaining in the blurred image frame may be generally attributedto spatially uncorrelated FPN. In this regard, following block 560, muchof the other noise or actual desired scene based information has beenremoved or excluded from the blurred image frame due to: intentionalblurring of the image frame (e.g., by motion or defocusing in blocks 520through 545), application of row and column FPN terms (block 555), andcontrast determination of (block 560).

Thus, it can be expected that following block 560, any remaining highspatial frequency content (e.g., exhibited as areas of contrast ordifferences in the blurred image frame) may be attributed to spatiallyuncorrelated FPN. Accordingly, in block 565, the blurred image frame ishigh pass filtered. In one embodiment, this may include applying a highpass filter to extract the high spatial frequency content from theblurred image frame. In another embodiment, this may include applying alow pass filter to the blurred image frame and taking a differencebetween the low pass filtered image frame and the unfiltered blurredimage frame to obtain the high spatial frequency content. In accordancewith various embodiments of the present disclosure, a high pass filtermay be implemented by calculating a mean difference between a sensorsignal (e.g., a pixel value) and its neighbors.

In block 570, a flat field correction process is performed on the highpass filtered blurred image frame to determine updated NUC terms (e.g.,if a NUC process has not previously been performed then the updated NUCterms may be new NUC terms in the first iteration of block 570).

For example, FIG. 7 illustrates a flat field correction technique 700 inaccordance with an embodiment of the disclosure. In FIG. 7, a NUC termmay be determined for each pixel 710 of the blurred image frame usingthe values of its neighboring pixels 712 to 726. For each pixel 710,several gradients may be determined based on the absolute differencebetween the values of various adjacent pixels. For example, absolutevalue differences may be determined between: pixels 712 and 714 (a leftto right diagonal gradient), pixels 716 and 718 (a top to bottomvertical gradient), pixels 720 and 722 (a right to left diagonalgradient), and pixels 724 and 726 (a left to right horizontal gradient).

These absolute differences may be summed to provide a summed gradientfor pixel 710. A weight value may be determined for pixel 710 that isinversely proportional to the summed gradient. This process may beperformed for all pixels 710 of the blurred image frame until a weightvalue is provided for each pixel 710. For areas with low gradients(e.g., areas that are blurry or have low contrast), the weight valuewill be close to one. Conversely, for areas with high gradients, theweight value will be zero or close to zero. The update to the NUC termas estimated by the high pass filter is multiplied with the weightvalue.

In one embodiment, the risk of introducing scene information into theNUC terms can be further reduced by applying some amount of temporaldamping to the NUC term determination process. For example, a temporaldamping factor λ between 0 and 1 may be chosen such that the new NUCterm (NUC_(NEW)) stored is a weighted average of the old NUC term(NUC_(OLD)) and the estimated updated NUC term (NUC_(UPDATE)). In oneembodiment, this can be expressed asNUC_(NEW)=λ·NUC_(OLD)+(1−λ)·(NUC_(OLD)+NUC_(UPDATE)).

Although the determination of NUC terms has been described with regardto gradients, local contrast values may be used instead whereappropriate. Other techniques may also be used such as, for example,standard deviation calculations. Other types flat field correctionprocesses may be performed to determine NUC terms including, forexample, various processes identified in U.S. Pat. No. 6,028,309 issuedFeb. 22, 2000, U.S. Pat. No. 6,812,465 issued Nov. 2, 2004, and U.S.patent application Ser. No. 12/114,865 filed May 5, 2008, which areincorporated herein by reference in their entirety.

Referring again to FIG. 5, block 570 may include additional processingof the NUC terms. For example, in one embodiment, to preserve the scenesignal mean, the sum of all NUC terms may be normalized to zero bysubtracting the NUC term mean from each NUC term. Also in block 570, toavoid row and column noise from affecting the NUC terms, the mean valueof each row and column may be subtracted from the NUC terms for each rowand column. As a result, row and column FPN filters using the row andcolumn FPN terms determined in block 550 may be better able to filterout row and column noise in further iterations (e.g., as further shownin FIG. 8) after the NUC terms are applied to captured images (e.g., inblock 580 further discussed herein). In this regard, the row and columnFPN filters may in general use more data to calculate the per row andper column offset coefficients (e.g., row and column FPN terms) and maythus provide a more robust alternative for reducing spatially correlatedFPN than the NUC terms which are based on high pass filtering to capturespatially uncorrelated noise.

In blocks 571-573, additional high pass filtering and furtherdeterminations of updated NUC terms may be optionally performed toremove spatially correlated FPN with lower spatial frequency thanpreviously removed by row and column FPN terms. In this regard, somevariability in infrared sensors 132 or other components of infraredimaging module 100 may result in spatially correlated FPN noise thatcannot be easily modeled as row or column noise. Such spatiallycorrelated FPN may include, for example, window defects on a sensorpackage or a cluster of infrared sensors 132 that respond differently toirradiance than neighboring infrared sensors 132. In one embodiment,such spatially correlated FPN may be mitigated with an offsetcorrection. If the amount of such spatially correlated FPN issignificant, then the noise may also be detectable in the blurred imageframe. Since this type of noise may affect a neighborhood of pixels, ahigh pass filter with a small kernel may not detect the FPN in theneighborhood (e.g., all values used in high pass filter may be takenfrom the neighborhood of affected pixels and thus may be affected by thesame offset error). For example, if the high pass filtering of block 565is performed with a small kernel (e.g., considering only immediatelyadjacent pixels that fall within a neighborhood of pixels affected byspatially correlated FPN), then broadly distributed spatially correlatedFPN may not be detected.

For example, FIG. 11 illustrates spatially correlated FPN in aneighborhood of pixels in accordance with an embodiment of thedisclosure. As shown in a sample image frame 1100, a neighborhood ofpixels 1110 may exhibit spatially correlated FPN that is not preciselycorrelated to individual rows and columns and is distributed over aneighborhood of several pixels (e.g., a neighborhood of approximately 4by 4 pixels in this example). Sample image frame 1100 also includes aset of pixels 1120 exhibiting substantially uniform response that arenot used in filtering calculations, and a set of pixels 1130 that areused to estimate a low pass value for the neighborhood of pixels 1110.In one embodiment, pixels 1130 may be a number of pixels divisible bytwo in order to facilitate efficient hardware or software calculations.

Referring again to FIG. 5, in blocks 571-573, additional high passfiltering and further determinations of updated NUC terms may beoptionally performed to remove spatially correlated FPN such asexhibited by pixels 1110. In block 571, the updated NUC terms determinedin block 570 are applied to the blurred image frame. Thus, at this time,the blurred image frame will have been initially corrected for spatiallycorrelated FPN (e.g., by application of the updated row and column FPNterms in block 555), and also initially corrected for spatiallyuncorrelated FPN (e.g., by application of the updated NUC terms appliedin block 571).

In block 572, a further high pass filter is applied with a larger kernelthan was used in block 565, and further updated NUC terms may bedetermined in block 573. For example, to detect the spatially correlatedFPN present in pixels 1110, the high pass filter applied in block 572may include data from a sufficiently large enough neighborhood of pixelssuch that differences can be determined between unaffected pixels (e.g.,pixels 1120) and affected pixels (e.g., pixels 1110). For example, a lowpass filter with a large kernel can be used (e.g., an N by N kernel thatis much greater than 3 by 3 pixels) and the results may be subtracted toperform appropriate high pass filtering.

In one embodiment, for computational efficiency, a sparse kernel may beused such that only a small number of neighboring pixels inside an N byN neighborhood are used. For any given high pass filter operation usingdistant neighbors (e.g., a large kernel), there is a risk of modelingactual (potentially blurred) scene information as spatially correlatedFPN. Accordingly, in one embodiment, the temporal damping factor λ maybe set close to 1 for updated NUC terms determined in block 573.

In various embodiments, blocks 571-573 may be repeated (e.g., cascaded)to iteratively perform high pass filtering with increasing kernel sizesto provide further updated NUC terms further correct for spatiallycorrelated FPN of desired neighborhood sizes. In one embodiment, thedecision to perform such iterations may be determined by whetherspatially correlated FPN has actually been removed by the updated NUCterms of the previous performance of blocks 571-573.

After blocks 571-573 are finished, a decision is made regarding whetherto apply the updated NUC terms to captured image frames (block 574). Forexample, if an average of the absolute value of the NUC terms for theentire image frame is less than a minimum threshold value, or greaterthan a maximum threshold value, the NUC terms may be deemed spurious orunlikely to provide meaningful correction. Alternatively, thresholdingcriteria may be applied to individual pixels to determine which pixelsreceive updated NUC terms. In one embodiment, the threshold values maycorrespond to differences between the newly calculated NUC terms andpreviously calculated NUC terms. In another embodiment, the thresholdvalues may be independent of previously calculated NUC terms. Othertests may be applied (e.g., spatial correlation tests) to determinewhether the NUC terms should be applied.

If the NUC terms are deemed spurious or unlikely to provide meaningfulcorrection, then the flow diagram returns to block 505. Otherwise, thenewly determined NUC terms are stored (block 575) to replace previousNUC terms (e.g., determined by a previously performed iteration of FIG.5) and applied (block 580) to captured image frames.

FIG. 8 illustrates various image processing techniques of FIG. 5 andother operations applied in an image processing pipeline 800 inaccordance with an embodiment of the disclosure. In this regard,pipeline 800 identifies various operations of FIG. 5 in the context ofan overall iterative image processing scheme for correcting image framesprovided by infrared imaging module 100. In some embodiments, pipeline800 may be provided by processing module 160 or processor 195 (both alsogenerally referred to as a processor) operating on image frames capturedby infrared sensors 132.

Image frames captured by infrared sensors 132 may be provided to a frameaverager 804 that integrates multiple image frames to provide imageframes 802 with an improved signal to noise ratio. Frame averager 804may be effectively provided by infrared sensors 132, ROIC 402, and othercomponents of infrared sensor assembly 128 that are implemented tosupport high image capture rates. For example, in one embodiment,infrared sensor assembly 128 may capture infrared image frames at aframe rate of 240 Hz (e.g., 240 images per second). In this embodiment,such a high frame rate may be implemented, for example, by operatinginfrared sensor assembly 128 at relatively low voltages (e.g.,compatible with mobile telephone voltages) and by using a relativelysmall array of infrared sensors 132 (e.g., an array of 64 by 64 infraredsensors in one embodiment).

In one embodiment, such infrared image frames may be provided frominfrared sensor assembly 128 to processing module 160 at a high framerate (e.g., 240 Hz or other frame rates). In another embodiment,infrared sensor assembly 128 may integrate over longer time periods, ormultiple time periods, to provide integrated (e.g., averaged) infraredimage frames to processing module 160 at a lower frame rate (e.g., 30Hz, 9 Hz, or other frame rates). Further information regardingimplementations that may be used to provide high image capture rates maybe found in U.S. Provisional Patent Application No. 61/495,879previously referenced herein.

Image frames 802 proceed through pipeline 800 where they are adjusted byvarious terms, temporally filtered, used to determine the variousadjustment terms, and gain compensated.

In blocks 810 and 814, factory gain terms 812 and factory offset terms816 are applied to image frames 802 to compensate for gain and offsetdifferences, respectively, between the various infrared sensors 132and/or other components of infrared imaging module 100 determined duringmanufacturing and testing.

In block 580, NUC terms 817 are applied to image frames 802 to correctfor FPN as discussed. In one embodiment, if NUC terms 817 have not yetbeen determined (e.g., before a NUC process has been initiated), thenblock 580 may not be performed or initialization values may be used forNUC terms 817 that result in no alteration to the image data (e.g.,offsets for every pixel would be equal to zero).

In blocks 818 and 822, column FPN terms 820 and row FPN terms 824,respectively, are applied to image frames 802. Column FPN terms 820 androw FPN terms 824 may be determined in accordance with block 550 asdiscussed. In one embodiment, if the column FPN terms 820 and row FPNterms 824 have not yet been determined (e.g., before a NUC process hasbeen initiated), then blocks 818 and 822 may not be performed orinitialization values may be used for the column FPN terms 820 and rowFPN terms 824 that result in no alteration to the image data (e.g.,offsets for every pixel would be equal to zero).

In block 826, temporal filtering is performed on image frames 802 inaccordance with a temporal noise reduction (TNR) process. FIG. 9illustrates a TNR process in accordance with an embodiment of thedisclosure. In FIG. 9, a presently received image frame 802 a and apreviously temporally filtered image frame 802 b are processed todetermine a new temporally filtered image frame 802 e. Image frames 802a and 802 b include local neighborhoods of pixels 803 a and 803 bcentered around pixels 805 a and 805 b, respectively. Neighborhoods 803a and 803 b correspond to the same locations within image frames 802 aand 802 b and are subsets of the total pixels in image frames 802 a and802 b. In the illustrated embodiment, neighborhoods 803 a and 803 binclude areas of 5 by 5 pixels. Other neighborhood sizes may be used inother embodiments.

Differences between corresponding pixels of neighborhoods 803 a and 803b are determined and averaged to provide an averaged delta value 805 cfor the location corresponding to pixels 805 a and 805 b. Averaged deltavalue 805 c may be used to determine weight values in block 807 to beapplied to pixels 805 a and 805 b of image frames 802 a and 802 b.

In one embodiment, as shown in graph 809, the weight values determinedin block 807 may be inversely proportional to averaged delta value 805 csuch that weight values drop rapidly towards zero when there are largedifferences between neighborhoods 803 a and 803 b. In this regard, largedifferences between neighborhoods 803 a and 803 b may indicate thatchanges have occurred within the scene (e.g., due to motion) and pixels802 a and 802 b may be appropriately weighted, in one embodiment, toavoid introducing blur across frame-to-frame scene changes. Otherassociations between weight values and averaged delta value 805 c may beused in various embodiments.

The weight values determined in block 807 may be applied to pixels 805 aand 805 b to determine a value for corresponding pixel 805 e of imageframe 802 e (block 811). In this regard, pixel 805 e may have a valuethat is a weighted average (or other combination) of pixels 805 a and805 b, depending on averaged delta value 805 c and the weight valuesdetermined in block 807.

For example, pixel 805 e of temporally filtered image frame 802 e may bea weighted sum of pixels 805 a and 805 b of image frames 802 a and 802b. If the average difference between pixels 805 a and 805 b is due tonoise, then it may be expected that the average change betweenneighborhoods 805 a and 805 b will be close to zero (e.g., correspondingto the average of uncorrelated changes). Under such circumstances, itmay be expected that the sum of the differences between neighborhoods805 a and 805 b will be close to zero. In this case, pixel 805 a ofimage frame 802 a may both be appropriately weighted so as to contributeto the value of pixel 805 e.

However, if the sum of such differences is not zero (e.g., evendiffering from zero by a small amount in one embodiment), then thechanges may be interpreted as being attributed to motion instead ofnoise. Thus, motion may be detected based on the average changeexhibited by neighborhoods 805 a and 805 b. Under these circumstances,pixel 805 a of image frame 802 a may be weighted heavily, while pixel805 b of image frame 802 b may be weighted lightly.

Other embodiments are also contemplated. For example, although averageddelta value 805 c has been described as being determined based onneighborhoods 805 a and 805 b, in other embodiments averaged delta value805 c may be determined based on any desired criteria (e.g., based onindividual pixels or other types of groups of sets of pixels).

In the above embodiments, image frame 802 a has been described as apresently received image frame and image frame 802 b has been describedas a previously temporally filtered image frame. In another embodiment,image frames 802 a and 802 b may be first and second image framescaptured by infrared imaging module 100 that have not been temporallyfiltered.

FIG. 10 illustrates further implementation details in relation to theTNR process of block 826. As shown in FIG. 10, image frames 802 a and802 b may be read into line buffers 1010 a and 1010 b, respectively, andimage frame 802 b (e.g., the previous image frame) may be stored in aframe buffer 1020 before being read into line buffer 1010 b. In oneembodiment, line buffers 1010 a-b and frame buffer 1020 may beimplemented by a block of random access memory (RAM) provided by anyappropriate component of infrared imaging module 100 and/or host device102.

Referring again to FIG. 8, image frame 802 e may be passed to anautomatic gain compensation block 828 for further processing to providea result image frame 830 that may be used by host device 102 as desired.

FIG. 8 further illustrates various operations that may be performed todetermine row and column FPN terms and NUC terms as discussed. In oneembodiment, these operations may use image frames 802 e as shown in FIG.8. Because image frames 802 e have already been temporally filtered, atleast some temporal noise may be removed and thus will not inadvertentlyaffect the determination of row and column FPN terms 824 and 820 and NUCterms 817. In another embodiment, non-temporally filtered image frames802 may be used.

In FIG. 8, blocks 510, 515, and 520 of FIG. 5 are collectivelyrepresented together. As discussed, a NUC process may be selectivelyinitiated and performed in response to various NUC process initiatingevents and based on various criteria or conditions. As also discussed,the NUC process may be performed in accordance with a motion-basedapproach (blocks 525, 535, and 540) or a defocus-based approach (block530) to provide a blurred image frame (block 545). FIG. 8 furtherillustrates various additional blocks 550, 552, 555, 560, 565, 570, 571,572, 573, and 575 previously discussed with regard to FIG. 5.

As shown in FIG. 8, row and column FPN terms 824 and 820 and NUC terms817 may be determined and applied in an iterative fashion such thatupdated terms are determined using image frames 802 to which previousterms have already been applied. As a result, the overall process ofFIG. 8 may repeatedly update and apply such terms to continuously reducethe noise in image frames 830 to be used by host device 102.

Referring again to FIG. 10, further implementation details areillustrated for various blocks of FIGS. 5 and 8 in relation to pipeline800. For example, blocks 525, 535, and 540 are shown as operating at thenormal frame rate of image frames 802 received by pipeline 800. In theembodiment shown in FIG. 10, the determination made in block 525 isrepresented as a decision diamond used to determine whether a givenimage frame 802 has sufficiently changed such that it may be consideredan image frame that will enhance the blur if added to other image framesand is therefore accumulated (block 535 is represented by an arrow inthis embodiment) and averaged (block 540).

Also in FIG. 10, the determination of column FPN terms 820 (block 550)is shown as operating at an update rate that in this example is 1/32 ofthe sensor frame rate (e.g., normal frame rate) due to the averagingperformed in block 540. Other update rates may be used in otherembodiments. Although only column FPN terms 820 are identified in FIG.10, row FPN terms 824 may be implemented in a similar fashion at thereduced frame rate.

FIG. 10 also illustrates further implementation details in relation tothe NUC determination process of block 570. In this regard, the blurredimage frame may be read to a line buffer 1030 (e.g., implemented by ablock of RAM provided by any appropriate component of infrared imagingmodule 100 and/or host device 102). The flat field correction technique700 of FIG. 7 may be performed on the blurred image frame.

In view of the present disclosure, it will be appreciated thattechniques described herein may be used to remove various types of FPN(e.g., including very high amplitude FPN) such as spatially correlatedrow and column FPN and spatially uncorrelated FPN.

Other embodiments are also contemplated. For example, in one embodiment,the rate at which row and column FPN terms and/or NUC terms are updatedcan be inversely proportional to the estimated amount of blur in theblurred image frame and/or inversely proportional to the magnitude oflocal contrast values (e.g., determined in block 560).

In various embodiments, the described techniques may provide advantagesover conventional shutter-based noise correction techniques. Forexample, by using a shutterless process, a shutter (e.g., such asshutter 105) need not be provided, thus permitting reductions in size,weight, cost, and mechanical complexity. Power and maximum voltagesupplied to, or generated by, infrared imaging module 100 may also bereduced if a shutter does not need to be mechanically operated.Reliability will be improved by removing the shutter as a potentialpoint of failure. A shutterless process also eliminates potential imageinterruption caused by the temporary blockage of the imaged scene by ashutter.

Also, by correcting for noise using intentionally blurred image framescaptured from a real world scene (not a uniform scene provided by ashutter), noise correction may be performed on image frames that haveirradiance levels similar to those of the actual scene desired to beimaged. This can improve the accuracy and effectiveness of noisecorrection terms determined in accordance with the various describedtechniques.

Referring now to FIG. 12, a block diagram is shown of a vehicle-mountedsystem 1200 for monitoring one or more occupants 1232 in an interiorcompartment 1230 of a vehicle in accordance with an embodiment of thedisclosure. Vehicle-mounted system 1200 may include one or more:infrared imaging modules 1202, processors 1204, memories 1206, alarmsirens 1208, communication modules 1210, seat position sensors 1212,and/or other components 1214. In various embodiments, components ofvehicle-mountable system 1200 may be implemented in the same or similarmanner as corresponding components of host device 102 of FIG. 1.Moreover, components of vehicle-mountable system 1200 may be configuredto perform various NUC processes and other processes described herein.

In some embodiments, infrared imaging module 1202 may be a small formfactor infrared camera or a small form factor infrared imaging deviceimplemented in accordance with various embodiments disclosed herein.Infrared imaging module 1202 may include an FPA implemented, forexample, in accordance with various embodiments disclosed herein orothers where appropriate.

Infrared imaging module 1202 may be configured to capture, process,and/or otherwise manage infrared images (e.g., including thermal images)of a desired portion of vehicle interior compartment 1230. In thisregard, infrared imaging module 1202 may be mounted anywhere in or on avehicle so that a desired portion of interior compartment 1230 is withina field of view (FOV) 1240 of infrared imaging module 1202. For example,infrared imaging module 1202 may be positioned so that at least aportion of occupant 1232 is within FOV 1240 when occupant 1232 ispresent and positioned in a seat 1234 of interior compartment 1230, asshown in FIG. 12.

In some embodiments, infrared imaging module 1202 may include one ormore optical elements 1203 (e.g., one or more: infrared-transmissivelenses, infrared-transmissive prisms, infrared-reflective mirrors,infrared fiber optics, or other optical elements) that guide infraredradiation from a desired portion of interior compartment 1230 to an FPAof infrared imaging module 1202. Optical elements 1203 may be usefulwhen it is difficult to mount infrared imaging module 1202 at a desiredangle and/or location. For example, mirrors and/or prisms may beutilized to provide an overhead perspective view of a passengercompartment even when it is not feasible to mount infrared imagingmodule 1202 at an angle looking down on the passenger compartment (e.g.,when mounting on a headliner with little or no room to tilt infraredimaging module 1202). Note also that optical elements 1203 may be usedto suitably define or alter an FOV of infrared imaging module 1202. Anadjustable FOV (e.g., selectable by infrared imaging module 1202 and/orprocessor 1204) may optionally be provided, which may be useful, forexample, when a close-up view of occupant 1232 is desired.

Infrared images captured, processed, and/or otherwise managed byinfrared imaging module 1202 may be radiometrically normalized infraredimages (e.g., thermal images). That is, pixels that make up the capturedimage may contain calibrated thermal data (e.g., temperature). Asdiscussed above in connection with infrared imaging module 100 of FIG.1, infrared imaging module 1202 and/or associated components may becalibrated using appropriate techniques so that images captured byinfrared imaging module 1202 are properly calibrated thermal images. Insome embodiments, appropriate calibration processes may be performedperiodically by infrared imaging module 1202 and/or processor 1204 sothat infrared imaging module 1202, and hence the thermal images capturedby it, may maintain proper calibration.

Radiometric normalization permits infrared imaging module 1202 and/orprocessor 1204 to efficiently detect, from the infrared images, objectshaving a specific range of temperature. Infrared imaging module 1202and/or processor 1204 may detect such objects efficiently andeffectively, because thermal images of objects having a specifictemperature may be easily discernable from a background and otherobjects, and yet less susceptible to lighting conditions or obscuring(e.g., obscured by clothing). In contrast, object detection operationsperformed on visible light images (e.g., images captured by CMOS or CCDsensors) or non-normalized infrared images, such as performing edgedetection and/or pattern recognition algorithms (e.g., using neuralnetworks) on such images, may be computationally complex yetineffective.

In one embodiment, infrared imaging module 1202 and/or processor 1204may be configured to detect contiguous regions of pixels (also referredto as “blobs” or “hot blobs”) having a temperature approximately in therange of a clothed person, for example, between approximately 75° F.(e.g., clothed part of a body) and approximately 110° F. (e.g., exposedpart of a body such as a face and hands). Such “hot blobs” may indicatepresence of persons in the thermal images, and may be analyzed furtheras described herein to ascertain the presence of one or more persons anddetermine various attributes associated with the detected persons.

Processor 1204 may be implemented as any appropriate processing deviceas described with regard to processor 195 in FIG. 1. In someembodiments, processor 1204 may be part of or implemented with otherconventional on-board processors that may be installed on a vehicle. Forexample, a modern vehicle may have a processor for controlling andmonitoring various mechanical operations of a vehicle, a processor for apassenger restraint system (e.g., an airbag system), a processor for avehicle security system (e.g., a theft alarm and tracking system), aprocessor for a vehicle telematics and accident notification system(e.g., OnStar™, Ford Sync™, BMW Assist™, and other similar systems), aprocessor for an on-board entertainment and vehicle information system,and/or a processor for a satellite navigation system, any of which maybe utilized to implement all or part of processor 1204. In otherembodiments, processor 1204 may interface and communicate with suchother conventional on-board processors and components associated withsuch processors.

Processor 1204 may be configured to interface and communicate with othercomponents of vehicle-mounted system 1200 to perform methods andprocesses described herein. Processor 1204 may be configured to receivethermal images of one or more desired portions of interior compartment1230 captured by one or more infrared imaging modules 1202. Processor1204 may be configured to perform, on the received thermal images andthe radiometric information contained therein, various thermal imageprocessing and analysis operations as further described herein to detectwhether one or more occupants are present in interior compartment 1230and determine one or more attributes associated with the detectedoccupants (e.g., occupant 1232).

In one embodiment, processor 1204 may be further configured to generateoccupant detection information based on the determination of thepresence and the attributes of one or more occupants (e.g., occupant1232). Based on the occupant detection information generated byprocessor 1204, vehicle-mounted system 1200 may perform various occupantmonitoring operations described herein. For example, processor 1204 maybe configured to detect an unwanted occupant (e.g., an intruder or aninfant left unattended) in an interior compartment (e.g., a passengercabin, a trunk, a cargo) of a vehicle based on the occupant detectioninformation when the vehicle is locked and parked. If an unwantedoccupant is detected, vehicle-mounted system 1200 may further respond bytriggering an alarm and/or disabling the vehicle ignition to preventtheft.

In other example, the occupant detection information may include thelocation of a driver's face and hands in the thermal images. Processor1204 may be configured to track the orientation and/or movement of thedriver's face and hands based on the occupant detection information todetermine whether the driver is inattentive or not, as further describedherein. If the driver is determined to be inattentive to driving,vehicle-mounted system 1200 may further respond by triggering an alarmand/or slowing down the vehicle.

In yet another example, the occupant detection information may include acount of the detected occupants as well as respective positions andapproximate body temperatures of the detected occupants. Processor 1204may be configured to generate, based at least in part on the occupantdetection information, occupant status information to be transmitted,for example, to a remote monitoring station for vehicle telematics andaccident notification systems (e.g., OnStar™, Ford Sync 911™, BMWAssist™, and other similar systems) in an event of a collision. Theoccupant status information may include the count, positions, bodytemperatures, health conditions of the occupants, and/or a user-viewableimage (e.g., a thermogram) of the interior compartment. In this regard,processor 1204 may be configured to determine the health condition ofthe occupant based on the body temperature and its variance. Further inthis regard, processor 1204 may be configured to convert the thermalimages into user-viewable images as further described herein. Suchuser-viewable images may be useful to rescue personnel in determiningthe status of vehicle occupants before and/or after the collision. Atleast part of the occupant status information may be stored in a memoryor storage device (e.g., memory 1206), so that it can be retrieved andtransmitted after a collision occurs.

In another embodiment, processor 1204 may be further configured togenerate appropriate control signals to adjust various vehiclecomponents based on the determination of the presence and the attributesof one or more occupants (e.g., occupant 1232). For example, processor1204 may generate appropriate control signals to adjust variousparameters for a passenger restraint system (e.g., airbags, seatbelts,and other passive and active restraints) based on whether or not anoccupant is found in a particular seat, the size of the occupant, and/orthe position of the occupant. Thus, for example, if an occupant of smallstature is seated near a certain airbag, the deployment timing may bedelayed, the deployment intensity may be reduced, and/or otherparameters for that airbag may be suitably adjusted to reduce injury tothe occupant in an event of a collision. Seatbelt tensioners maysimilarly be adjusted and/or disabled based on whether or not anoccupant is found in a particular seat, the size of the occupant, and/orthe position of the occupant.

In another example, processor 1204 may generate appropriate controlsignals to adjust various climate settings (e.g., to control individualvent openings and to control temperature and volume of air flowingthrough the individual vent openings) in a vehicle heating, ventilation,and air conditioning (HVAC) system, based on the number of occupants,respective positions of occupants, respective body temperatures ofoccupants, and/or the ambient temperature of an interior compartment. Inthis regard, processor 1204 may further be configured to determine theambient temperature of an interior compartment from thermal images of atleast a portion of the interior compartment capture by infrared imagingmodule 1202, as further described herein.

In yet another example, processor 1204 may generate appropriate controlsignals for motorized seat, steering column, and pedal adjusters, so asto adjust the fore-and-aft position, height, and/or angle of the seat(e.g., seat 1234), steering column, and/or pedals based on thedetermined size and/or position of an occupant. For example, if adriving seat is positioned too far back relative to the determined sizeof the driver, processor 1204 may generate a control signal to moved theseat forward. It is also contemplated that other vehicle components,such as an on-board entertainment system (e.g., audio, video monitors,or other audio visual components), may be controlled by processor 1204based on the determined presence and attributes of occupants in aninterior compartment of a vehicle.

Memory 1206 may include one or more memory devices to store data andinformation, including thermal images, occupant detection information,and occupant status information. The one or more memory devices mayinclude various types of memory for thermal image and other informationstorage including volatile and non-volatile memory devices, such as RAM(Random Access Memory), ROM (Read-Only Memory), EEPROM(Electrically-Erasable Read-Only Memory), flash memory, a disk drive. Inone embodiment, occupant status information may be periodicallygenerated and stored in the one or more memory devices. Such storedstatus information may be retrieved and transmitted (e.g., to a remotemonitoring station for accident notification systems, to a mobiledevice, or to other external devices) in an event of a collision to helpemergency responders in rescuing occupants of a vehicle. In someembodiments, processor 1204 may be configured to execute softwareinstructions stored on memory 1206 to perform various methods,processes, or operations in the manner described herein.

Alarm sirens 1208 may be implemented with various speakers, horns,bells, chimes, flashers, lights, or other appropriate devices forsounding various alarms generated by processor 1204. Alarm sirens 1208may be sized, disposed, or otherwise adapted to warn occupants in aninterior compartment (e.g., to warn inattentive drivers) or may besized, disposed, otherwise adapted to emit lights and/or soundsexternally (e.g., security system sirens to thwart or warn ofintruders). In some embodiments, alarm sirens 1208 may be implemented ona key fob for remotely locking and unlocking vehicles, so that a driveraway from the vehicle may be warned of alarms generated by processor1204. It is contemplated that existing alarm sirens (e.g., for a vehiclesecurity system), horns, chimes, lights, and/or flashers may be utilizedas alarm sirens 1208.

Communication module 1210 may be configured to handle communication andinterfacing between various components of vehicle-mounted system 1200.For example, components such as infrared imaging module 1202, alarmsirens 1208, seat position sensors 1212 and/or other components 1214 maytransmit and receive data to and from processor 1204 throughcommunication module 1210, which may manage wired and/or wirelessconnections (e.g., through proprietary RF links, proprietary infraredlinks, and/or standard wireless communication protocols such as IEEE802.11 WiFi standards and Bluetooth™) between the various components.

Communication module 1210 may also be configured to allow components ofvehicle-mounted system 1200 to communicate and interface with otherexisting vehicle electronic components. For example, processor 1204 maycommunicate, via communication module 1210, with a vehicle electroniccontrol unit (ECU), a passenger restraint system, a vehicle telematicsand accident notification system, an in-vehicle information andentertainment system, a satellite navigation system, and other existingsensors and electronic components. In this regard, communication module1210 may support various interfaces, protocols, and standards forin-vehicle networking, such as the controller area network (CAN) bus,the vehicle area network (VAN) standard, the local interconnect network(LIN) bus, the media oriented systems transport (MOST) network, the ISO11738 (or ISO bus) standard.

Communication module 1210 may be further configured to allow componentsof vehicle-mounted system 1200 to communicate with external devices overvarious wireless telecommunication networks, such as code divisionmultiple access (CDMA) networks, enhanced data rates for GSM evolution(EDGE) networks, universal mobile telephone system (UMTS) networks,general packet radio service (GPRS) networks, high-speed downlink packetaccess (HSDPA) networks, and/or other appropriate networks. For example,processor 1204 may communicate occupant status information to remotemonitoring stations, mobile devices, or other networked computers anddevices via communication module 1210 over such wirelesstelecommunication networks. In another example, processor 1204 maytransmit various alarms generated by processor 1204 as further describedherein to various external devices via communication module 1210.

In some embodiments, vehicle-mounted system 1200 may comprise as manysuch communication modules 1210 as desired for various applications ofvehicle-mounted system 1200 on various types of vehicle. In otherembodiments, communication module 1210 may be integrated into orimplemented as part of various other components of vehicle-mountedsystem 1200. For example, infrared imaging module 1202 and processor1204 may each comprise a subcomponent that may be configured to performthe operations of communication module 1210, and may communicate withone another via wired and/or wireless connection without separatecommunication module 1210.

Seat position sensors 1212 may include one or more devices that may beconfigured to detect the fore-and-aft position, angle, and/or height ofa seat (e.g., seat 1234). Seat position sensors 1212 may be implementedin any appropriate manner, including attaching mechanical switches,magnetometric sensors (e.g., Hall effect sensors), or other types oftransducers to a seat track, seat back, and/or other suitable locations.The detected position, angle, and/or height of a seat may be used byinfrared imaging module 1202 and/or processor 1204 to perform scalecalibration of the thermal images. Because the size and/or position ofan occupant within the captured thermal images may vary depending on theseat position, calibrating scaling information (e.g., correspondencebetween the size within thermal images to the actual size) usinginformation from seat position sensors 1212 may provide a more accurateestimation of the size and/or position of occupants.

Other components 1214 may include any other device or sensor as may bedesired for various applications of vehicle-mounted system 1200. In someembodiments, other components 1214 may include a passenger restraintsystem, motorized seat adjusters, an automatic HVAC system, and othervehicle components that may desirably be adjusted by vehicle-mountedsystem 1200 based on the presence and attributes of occupants asdescribed above. In some embodiments, other components 1214 may includean ambient temperature sensor (e.g., a thermocouple, a thermometer), anoccupant weight sensor, and other sensors that may provide referencedata points for calibrating or verifying the various thermal imageanalytics described herein.

In various embodiments, one or more components of vehicle-mounted system1200 may be combined and/or implemented or not, as desired or dependingon application requirements. For example, processor 1204 may be combinedwith infrared imaging module 1202, memory 1206, and/or communicationmodule 1210. In another example, processor 1204 may be combined withinfrared imaging sensor 1202 with only certain operations of processor1204 performed by circuitry (e.g., processor, logic device,microprocessor, microcontroller, etc.) within infrared imaging module1202.

Thus, vehicle-mounted system 1200 may be mounted on, installed in, orotherwise integrated into a vehicle to provide comprehensive monitoringof occupants. By capturing, processing, and analyzing thermal images ofinterior compartments, vehicle-mounted system 1200 may determine variousattributes of occupants and/or environmental conditions of the interiorcompartments. Such comprehensive monitoring information may bebeneficially used in a variety of situations including, but not limitedto, detecting intruders or other unwanted occupants while a vehicle islocked and parked, providing detailed occupant status information in anevent of an accident, warning inattentive drivers while a vehicle isbeing driven, and adjusting various vehicle components. In contrast,conventional sensors cannot provide such comprehensive monitoring ofoccupants, even when various types of sensors (e.g., occupant weightsensors, transducer-type sensors, motion sensors, seat position sensors,temperature sensors, and other sensors found in a vehicle interiorcompartment) are used in combination.

FIGS. 13A-13B show a vehicle 1300 having vehicle-mounted system 1200 formonitoring occupants 1332A-1332E in interior compartments 1330A-1330B ofvehicle 1300 in accordance with an embodiment of the disclosure. Morespecifically, FIG. 13A illustrates a side view of vehicle 1300 havingvehicle-mounted system 1200 monitoring a passenger compartment (interiorcompartment 1330A) and a trunk (interior compartment 1330B, which may beany enclosed or open cargo area), and FIG. 13B illustrates a top view ofvehicle 1300.

In one embodiment, a plurality of infrared imaging modules 1202, shownin FIG. 13A-13B as infrared imaging modules 1202A-1202B, may be disposedat appropriate locations in passenger compartment 1330A so thatoccupants in each row of seats may be within an FOV of at least one ofinfrared imaging modules 1202A-1202B. Infrared imaging module 1202C mayalso be positioned at an appropriate location so that trunk 1330B iswithin its FOV, as shown in FIG. 13A-13B. Placement of infrared imagingmodule 1203C for monitoring trunk 1330B allows detection of unwantedoccupant 1332E (e.g., intruders or trapped persons and animals) that maybe present in trunk 1330B.

In other embodiments, more or less infrared imaging modules 1202 may bemounted in interior compartments 1330A-1330B as appropriate for variousapplications of vehicle-mounted system 1200. For example, four infraredimaging modules 1202 may be utilized and each positioned to cover eachone of occupants 1332A-1332D rather than each row of seats. In anotherembodiment, one infrared imaging module 1202 may be positioned to covermultiple rows of seats within its FOV, for example, when appropriatemounting locations that permit a wide overhead view of interiorcompartment 1330A are available.

It should be appreciated that although infrared imaging modules1202A-1202B are shown in FIG. 13A-13B as being mounted on a ceiling ofpassenger compartment 1330A, infrared imaging modules 1202 may bemounted on or at any other location (e.g., pillar, dashboard, seatback,floor) to capture desired portions of interior compartment 1330A.Moreover, although vehicle 1300 is depicted as an automobile,vehicle-mounted system 1200 may be mounted on, installed in, orotherwise integrated into various other types of vehicles, such as anautobus, a cargo truck, a train, an airliner, or any other vehiclehaving one or more interior compartments that may be monitored byvehicle-mounted system 1200.

It should also be appreciated that compared with conventional sensors(e.g., pressure/weight sensors integrated into seats, visible lightimaging sensors such as CCD or CMOS sensors, or other transducersmounted in interior compartments), utilizing infrared imaging modules1202 (e.g., an arrangement of infrared imaging modules 1202A-1202C asshown in FIG. 13A-13B) permits more accurate detection of occupantswhile permitting a smaller number of sensor modules to be mounted.

For example, thermal images captured by just one infrared imaging module(e.g., infrared imaging module 1202B) may contain images of thermalradiation from any number of occupants within its FOV, including aninfant (e.g., occupant 1332D) in an infant car seat. As furtherdescribed herein, radiometric information contained in such thermalimages may facilitate detection of presence and attributes (e.g.,approximate position, size, and body temperature) of any number ofobjects having certain radiometric properties. Thus, for example,processor 1202 may be able to detect the presence and attributes of bothoccupant 1332C and infant 1332D (e.g., detected as a smaller “blob” butstill having a surface temperature of a person) from thermal imagescaptured by infrared imaging module 1202B. In contrast, conventionalsensors (e.g., weight/pressure sensors, ultrasonic sensors and othersimilar transducers), even when mounted at multiple locations, may failto detect infants or other occupants that do not exceed certainsize/weight thresholds, and conversely may falsely indicate presence ofan occupant when large objects (e.g., luggage) are present.

Referring now to FIG. 14, a flowchart is illustrated of a process 1400for monitoring occupants in an interior compartment of a vehicle inaccordance with an embodiment of the disclosure. For example, process1400 may be performed by vehicle-mounted system 1200 mounted on or invehicle 1300. It should be appreciated that vehicle-mounted system 1200and vehicle 1300 are identified only for purposes of giving examples andthat any other suitable system may be mounted on any other suitablevehicle to perform all or part of process 1400.

At block 1402, thermal images (e.g., containing pixels with radiometricdata) of desired portions of a vehicle interior compartment may becaptured by one or more infrared imaging modules 1202 mounted in or on avehicle. For example, thermal images containing images of thermalradiation from occupants 1332A-1332E, if present, may be captured byinfrared imaging modules 1202A-1202C, as shown in FIGS. 13A-13B. Thethermal images may be received, for example, at processor 1204 that iscommunicatively coupled to one or more infrared imaging modules 1202 viawired or wireless links. At block 1404, an NUC process may be performedon the captured thermal images to remove noise therein, for example, byusing various NUC techniques disclosed herein.

In one embodiment, scale calibration may be performed at block 1406, forexample, by processor 1204 and/or infrared imaging module 1202 based onthe fore-and-aft position, angle, and/or height of an adjustable seat(e.g., seat 1234) as detected by seat position sensors 1212. Someoperations of process 1400 may rely on scaling information (e.g.,correspondence between the size within thermal images to the actualsize) in determining the presence, size, and/or position of occupants.Because the size and/or position of a seated occupant within thecaptured thermal images may vary depending on the seat position, scalecalibration may appropriately adjust such scaling information so thatvarious operations of process 1400 may determine the presence andvarious attributes of occupants with greater accuracy.

In other embodiments, scale calibration may be performed before block1402 or block 1404 rather than at block 1406. Also, as will beappreciated, scale calibration may sometimes be performed only when theseat position has changed. In various embodiments, scale calibration maybe omitted from process 1400. For example, if the error due to scalingis negligible or if the seat position is fixed, scale calibration may beomitted without affecting other operations of process 1400.

At block 1408, the presence of one or more occupants may be determinedfrom the thermal images. For example, in one embodiment, regions ofcontiguous pixels having temperature values approximately in the rangeof a surface temperature of a clothed person may be detected from theradiometrically calibrated thermal images. Such regions (or “blobs”) mayindicate occupants in the portion of the interior compartmentrepresented by the thermal images. The thermal images and the blobsdetected therein may be further processed and/or analyzed, for example,by performing various filtering operations and comparing the size andshape of the blobs to those of a human figure, to ascertain whether oneor more occupants are present.

In another embodiment, the thermal images may be analyzed to detect oneor more objects, for example, using background modeling techniques, edgedetection techniques, or other object detection techniques suitable foruse with thermal images. The radiometric properties (e.g., surfacetemperature) of the detected objects may then be analyzed usingradiometric data contained in the thermal images for further determiningwhether the objects correspond to human occupants. For example, theapproximate temperatures of the detected objects may be determined fromthe thermal images and compared against a temperature range of a clothedperson. If a surface temperature of a detected object corresponds tothat of a clothed person, the object more likely represent a humanoccupant. The size and shape of the object may also be analyzed. Basedon the size, the shape, and the radiometric properties, it may beascertained whether the object is a human occupant or not.

In one aspect of such an embodiment, background modeling techniques maybe used to detect objects in a vehicle interior compartment. Because thebackground scene (e.g., an empty passenger compartment) of an interiorcompartment rarely changes and because thermal images are generallyinsensitive to changing lighting conditions, a background model (e.g.,pixels that belong to a background scene) may be constructed with highaccuracy, and a region of pixels different from the background (alsoreferred to as a “region of interest”) may easily be distinguished as aprobable foreground object. As described above, the radiometricproperties of such a region of interest (ROI) may then be analyzed tofurther ascertain whether the detected ROI likely represent a humanoccupant or not.

In various embodiments, the various processing and analysis operationsdescribed for block 1408 may be omitted or included, and may beperformed in any other order as appropriate for determining presence ofoccupants in an interior compartment of a vehicle. For example, in someembodiments, detecting hot “blobs” may be sufficient to determinepresence of occupants, whereas in other embodiments various thermalimage analytics may be performed in combination to increase accuracy ofdetection.

If one or more occupants are detected at block 1408, various attributesassociated with the detected occupants may be determined at block 1410.Taking into account which portions of the vehicle interior compartment(e.g., predetermined depending on the mounting location of infraredimaging modules 1202) are represented in the thermal images and based oncoordinates of the detected occupants within the thermal images,positions of the one or more occupants may be determined. For example,an occupant may be detected as present on a driver's seat by analyzingthermal images of front row seats of the interior compartment. Inanother example, a passenger may be detected as present at a certaindistance from the door in the rear passenger seat.

The approximate locations of the head, the face, and/or the hands of thedetected occupants may be further localized. Because faces or hands aregenerally exposed (i.e., not covered by clothing), the approximatelocations of such parts of the occupants' bodies may be determined bylocating the areas with temperatures close to that of an exposed skinarea. In some embodiments, the approximate location of the eyes may alsobe determined. The eyes, whether open or closed, exhibit a highertemperature than the rest of the facial area. Also, if glasses are wornover the eye area, they exhibit much a lower temperature than the restof the facial area in the thermal images because glasses do notgenerally transmit thermal radiation. The location of the eyes may bedetermined by localizing such temperature variations in the facial area.In some embodiments, the approximate body temperatures of the detectedoccupants may also be determined from the exposed skin areas of theoccupants.

The approximate sizes of the detect occupants may also be determined. Inone embodiment, the approximate sizes of the occupants may be determinedusing scaling information and/or proportionality information. Asdescribed above with respect to block 1406, scaling information relatesto the correspondence between the size within thermal images to theactual size, and may be calibrated if desired. Proportionalityinformation may indicate the correspondence between the portion ofoccupant's body contained within the thermal image to the estimated fullsize of the occupant. For example, if due to the mounting location ofinfrared imaging modules the thermal images contain thermal radiation ofonly the upper body of an occupant, proportionality information may beused estimate the whole body size. Proportionality information may alsobe used to correct for the distorted aspect ratio in an overheadperspective view of occupants. Scaling information and/orproportionality information may not be needed, however, if only a roughestimation of sizes are desired. In other embodiments, rough sizeestimate may be obtained from the pixel count of the detected occupantsin thermal images.

At block 1412, various conditions associated with the interiorcompartment and/or the vehicle may be determined. In one embodiment, theambient temperature of the interior compartment may be determined fromthe thermal images. For example, the ambient temperature may bedetermined by obtaining the surface temperature of a target object ofknown emissivity. The target object may be placed at a location in theinterior compartment such that the thermal radiation from the targetobject may be imaged at predetermined coordinates in the thermal images.The target object may be an object placed in the interior compartmentfor the purpose of obtaining an ambient temperature, or it may be anypreexisting object or part of a preexisting object (e.g., a particulararea of a headliner). In another embodiment, a conventional temperaturesensor may be used to determine the ambient temperature in place of, orin addition to, the ambient temperature detection operation using thethermal images.

Other vehicle conditions that may be determined at block 1412 include,but not limited to, whether or not a vehicle collision has occurred,whether the vehicle is moving above a certain speed, and whether or notthe vehicle is locked and parked. In one embodiment, conventionalmotion/shock sensors (e.g., collision sensors coupled to an airbagsystem) may be polled to detect an occurrence of a vehicle collision.If, for example, it is determined that a vehicle collision has occurred,vehicle-mounted system 1200 may transmit occupant-related information toremote monitoring stations and other external devices so as to aidemergency responders in the rescue effort, as further described herein.In one embodiment, whether or not the vehicle is locked and parked maybe determined by polling a vehicle lock mechanism and/or a vehiclesecurity system of the vehicle. If, for example, it is determined thatthe vehicle is locked and parked, vehicle-mounted system 1200 maymonitor the interior compartment for intruders or other unwantedoccupants. In one embodiment, whether or not the vehicle is being drivenabove a certain speed may be determined by polling a vehicle speedsensor. If, for example, it is determined that the vehicle is movingabove a certain threshold speed, vehicle-mounted system 1200 may track adriver's face and/or hands to detect an inattentive driver, as furtherdescribed herein. The threshold speed may be chosen to be any speed atwhich inattentive driving may pose a danger.

At block 1414, occupant detection information, control signals foradjusting various components, and/or other monitoring information may begenerated based on the determination of the presence of the one or moreoccupants, the attributes associated with the detected occupants, and/orthe vehicle conditions. In one embodiment, the occupant detectioninformation may include an indication of whether or not one or moreoccupants are detected, a count of the detected occupants, and variousoccupant attributes described above in connection with block 1410.Similarly, control signals to adjust various components (e.g., apassenger restraint system, a HVAC system, and motorized seat adjusters)may be generated based on the determination of the presence of the oneor more occupants, the attributes associated with the detectedoccupants, and/or the vehicle conditions.

In one embodiment, user-viewable thermal images (e.g., thermograms) maybe generated by converting the thermal images using appropriate methodsand algorithms. For example, the thermal data (e.g., temperature data)contained in the pixels of the thermal images may be converted intogray-scaled or color-scaled pixels to construct images that can beviewed by a person. User-viewable thermal images may optionally includea legend or scale that indicates the approximate temperature ofcorresponding pixel color and/or intensity. Such user-viewable images ofthe interior compartment may be transmitted to and viewed by an owner ofthe vehicle and/or other appropriate persons for a better understandingof the occupant detection information, for example, when an unwantedoccupant may be present or when a vehicle collision has occurred. Othermonitoring information may also be generated as further describedherein.

At block 1416, various types of information and data generated inprocess 1400 may be stored in a memory (e.g., memory 1206). The storedinformation may be recalled and retrieved, for example, to reviewdetected intrusions or to transmit to emergency responder services in anevent of an accident.

At block 1418, various actions may be taken in response to, or based on,the occupant detection information, the detected vehicle conditions,and/or the control signals. For example, in various embodiments, variousvehicle components and subsystems including, but not limited to, apassenger restraint system, a HVAC system, an on-board entertainmentsystem, and motorized seat, steering column and pedal adjusters may beadjusted in response to or based on the generated control signals, asdescribed above in connection with processor 1204 of FIG. 12. Also invarious embodiments, various alarms may be generated based on theoccupant detection information and/or the vehicle condition, asdescribed further herein.

FIG. 15 illustrates a process 1500 for performing various monitoringoperations based on occupant detection information in accordance with anembodiment of the disclosure. For example, process 1500 may be performedas part of process 1400 of FIG. 14, such as at block 1414 (e.g.,generate various types of information) and/or at block 1418 (e.g., takeaction based on generated information).

At block 1502, the vehicle condition from process 1400 may be queried tocheck whether the vehicle is locked and parked. If so, the occupantdetection information from process 1400 may be queried at block 1504 tocheck whether one or more occupants are detected in the vehicle interiorcompartment. If one or more occupants are detected, an alarm may begenerated at block 1506 to warn of unwanted occupants in the vehicleinterior compartment. The generated alarm may be transmitted to a keyfob, a remote monitoring station, or other external devices such as amobile phone, so that an owner of the vehicle and/or other appropriatepersons may be warned. Also, alarm sirens (e.g., alarm sirens 1208) maybe used to sound sirens and flash lights. At block 1508, the vehicleignition may be disabled to prevent a possible vehicle theft. It will beappreciated that intruder detection based on the occupant detectioninformation permits detection of unscrupulous intruders who may not bedetected under conventional shock/motion based security system sensors,since such intruders may stay still lurking inside the vehicle aftergaining entrance to the vehicle. By staying still, an intruder may avoidtriggering conventional sensors, but may not avoid being detected bysystems and methods described herein due to the heat signature given offby the intruder.

If it is determined at block 1502 that the vehicle is not parked butbeing driven, the vehicle condition may be further queried at block 1510to check whether a collision has occurred or not. If so, occupant statusinformation may be generated at block 1512. In one embodiment, theoccupant status information may be generated based on various currentand stored information generated through process 1400, including theposition and the count of the occupants, user-viewable thermal images ofthe vehicle interior compartment, and the approximate body temperaturesof the occupants. In some embodiments, the health conditions of theoccupants may be determined by further analyzing the approximate bodytemperatures of the occupants and the thermal images. The healthconditions may then be included in the occupant status information. Forexample, the occupant status information may indicate that an occupantis in critical condition if the body temperature is below a normalrange, and/or it may indicate that an occupant is bleeding if theclothed area of an occupant's body exhibits patches of high bodytemperature.

At block 1514, the generated occupant status information may betransmitted, for example, to a remote monitoring station for vehicletelematics and accident notification systems (e.g., OnStar™, Ford Sync911™, BMW Assist™, and other similar systems) in an event of a collisionto aid emergency responders in their rescue effort. The occupant statusinformation may be transmitted to other external devices, such as amobile phone or a networked computer.

If it is determined at block 1510 that the vehicle is not involved in acollision, the vehicle condition may be further queried at block 1516 tocheck whether the vehicle is being driven above a threshold speed. Ifso, the driver's face and/or hands may be tracked based on the occupantdetection information at block 1518. As described above with respect toblock 1410 of FIG. 14, the location of the driver's face, eyes, andhands may be determined by analyzing the thermal images and theradiometric data contained therein. The orientation and movement of thedriver's face and hands may be tracked using the location information.At block 1520, the tracked orientation and movement of the driver's faceand/or hands may be analyzed to determine whether the driver isinattentive or not. For example, the driver may be inattentive if thehands are not on the steering wheel for a certain duration and/or if theeyes are not directed to the road ahead for a certain duration. If it isdetermine that the driver may be inattentive at block 1522, an alarm maybe generated at block 1524 to warn the driver to focus on driving.

Therefore, it will be appreciated that process 1400 may generatecomprehensive occupant detection information by capturing, processing,and analyzing thermal images and the radiometric data contained therein.Such comprehensive occupant detection information may be advantageouslyused by operations of process 1500 to provide monitoring of an interiorcompartment of a vehicle and occupants therein for a variety ofsituations.

Where applicable, various embodiments provided by the present disclosurecan be implemented using hardware, software, or combinations of hardwareand software. Also where applicable, the various hardware componentsand/or software components set forth herein can be combined intocomposite components comprising software, hardware, and/or both withoutdeparting from the spirit of the present disclosure. Where applicable,the various hardware components and/or software components set forthherein can be separated into sub-components comprising software,hardware, or both without departing from the spirit of the presentdisclosure. In addition, where applicable, it is contemplated thatsoftware components can be implemented as hardware components, andvice-versa.

Software in accordance with the present disclosure, such asnon-transitory instructions, program code, and/or data, can be stored onone or more non-transitory machine readable mediums. It is alsocontemplated that software identified herein can be implemented usingone or more general purpose or specific purpose computers and/orcomputer systems, networked and/or otherwise. Where applicable, theordering of various steps described herein can be changed, combined intocomposite steps, and/or separated into sub-steps to provide featuresdescribed herein.

Embodiments described above illustrate but do not limit the invention.It should also be understood that numerous modifications and variationsare possible in accordance with the principles of the invention.Accordingly, the scope of the invention is defined only by the followingclaims.

What is claimed is:
 1. A vehicle-mountable thermal imaging systemcomprising: an infrared imaging device configured to be installed in aninterior compartment of a vehicle and comprising a focal plane array(FPA) configured to capture thermal images comprising pixelsrepresenting thermal radiation variations in at least a portion of theinterior compartment; and a processor configured to: analyze the thermalradiation variations represented in the pixels of the thermal images;detect one or more regions-of-interest (ROIs) in the thermal imagesbased on the analysis of the thermal radiation variations; analyzegeometric and thermal properties of the one or more detected ROIs;determine, based on the analysis of the geometric and thermal propertiesof the detected ROIs, temperature profiles of one or more objectspresent in the portion of the interior compartment and approximate sizesand/or shapes of the one or more objects; and determine whether one ormore unwanted occupants are present in the interior compartment based onthe determination of the temperature profiles and the approximate sizesand/or shapes of the one or more objects.
 2. The vehicle-mountablethermal imaging system of claim 1, wherein the processor is configuredto identify infants, small children, small animals, or intruders as theone or more unwanted occupants.
 3. The vehicle-mountable thermal imagingsystem of claim 1, wherein the processor is further configured togenerate an alarm in response to determining that the one or moreunwanted occupants are present in the interior compartment.
 4. Thevehicle-mountable thermal imaging system of claim 3, further comprisinga network interface controller (NIC) configured to manage wirelesscommunications with external devices, wherein the processor is furtherconfigured to transmit the alarm to at least one of an on-board securitysystem, a key fob, a remote monitoring station, a mobile phone, or anetworked computer via the NIC.
 5. The vehicle-mountable thermal imagingsystem of claim 4, wherein the processor is further configured totransmit the thermal images to at least one of the on-board securitysystem, key fob, remote monitoring station, mobile phone, or networkedcomputer via the NIC to be converted into user-viewable thermal imagesfor viewing by a user.
 6. The vehicle-mountable thermal imaging systemof claim 1, wherein the processor is further configured to: determine acondition of the vehicle, including whether the vehicle is parked,moving, or in a collision; and determine whether the one or moreunwanted occupants are present in the interior compartment further basedon the determined condition of the vehicle.
 7. The vehicle-mountablethermal imaging system of claim 6, further comprising a networkinterface controller (NIC) configured to manage wireless communicationswith external devices, the processor is further configured to: generatevehicle occupant information including corresponding positions of one ormore occupants and a count of the one or more occupants based on thedetermination of the temperature profiles and the approximate sizesand/or shapes of the one or more objects; and transmit, in responsedetermining that the vehicle is in a collision, the generated vehicleoccupant information to at least one of a remote monitoring station, amobile phone, or a networked computer via the NIC.
 8. Thevehicle-mountable thermal imaging system of claim 6, wherein theprocessor is further configured to generate a vehicle disable signal todisable the vehicle in response to determining that the vehicle ismoving and that the one or more unwanted occupants are present.
 9. Thevehicle-mountable thermal imaging system of claim 1, wherein the thermalimages captured by the infrared imaging device are radiometricallynormalized thermal images such that the pixels represent calibratedtemperature data.
 10. The vehicle-mountable thermal imaging system ofclaim 8, the infrared imaging device comprises a shutter used as atemperature reference in a periodic calibration process for radiometricnormalization of captured thermal images.
 11. A vehicle comprising thevehicle-mountable thermal imaging system of claim
 1. 12. A method ofmonitoring an interior compartment of a vehicle, the method comprising:capturing, using a focal plane array (FPA) of an infrared imagingdevice, thermal images comprising pixels representing thermal radiationvariations in at least a portion of an interior compartment of avehicle, wherein the infrared imaging device is mounted in or on thevehicle so that the at least a portion of the interior compartment iswithin a field of view (FOV) of the infrared imaging device; analyzingthe thermal radiation variations represented in the pixels of thethermal images; detecting one or more regions-of-interest (ROIs) in thethermal images based on the analysis of the thermal radiationvariations; analyzing geometric and thermal properties of the one ormore detected ROIs; determining, based on the analysis of the geometricand thermal properties of the detected ROIs, temperature profiles of oneor more objects present in the portion of the interior compartment andapproximate sizes and/or shapes of the one or more objects; anddetermining whether one or more unwanted occupants are present in theinterior compartment based on the determination of the temperatureprofiles and the approximate sizes and/or shapes of the one or moreobjects.
 13. The method of claim 12, wherein the determining of whetherone or more unwanted occupants are present comprises identifyinginfants, small children, small animals, or intruders as the one or moreunwanted occupants.
 14. The method of claim 12, further comprisinggenerating an alarm in response to determining that the one or moreunwanted occupants are present in the interior compartment.
 15. Themethod of claim 13, further comprising wirelessly transmitting the alarmto at least one of an on-board security system, a key fob, a remotemonitoring station, a mobile phone, or a networked computer.
 16. Themethod of claim 12, further comprising wirelessly transmitting thethermal images to at least one of an on-board security system, a keyfob, a remote monitoring station, a mobile phone, or a networkedcomputer to be converted into user-viewable thermal images for viewingby a user.
 17. The method of claim 12, further comprising determining acondition of the vehicle, including whether the vehicle is parked,moving, or in a collision, wherein the determining of whether the one ormore unwanted occupants are present is further based on the determinedcondition of the vehicle.
 18. The method of claim 17, furthercomprising: generating vehicle occupant information includingcorresponding positions of one or more occupants and a count of the oneor more occupants based on the determination of the temperature profilesand the approximate sizes and/or shapes of the one or more objects; andwirelessly transmitting, in response determining that the vehicle is ina collision, the generated vehicle occupant information to at least oneof a remote monitoring station, a mobile phone, or a networked computer.19. The method of claim 17, further comprising generating a vehicledisable signal to disable the vehicle in response to determining thatthe vehicle is moving and that the one or more unwanted occupants arepresent.
 20. The method of claim 12, wherein: the thermal images areradiometrically normalized thermal images such that the pixels representcalibrated temperature data; and the method further comprisesperiodically and automatically calibrating the infrared imaging devicefor radiometric normalization of the thermal images.